Information processing apparatus, information processing method, and program

ABSTRACT

An information processing apparatus includes: a soma-related information storage unit in which two or more pieces of soma-related information having a soma identifier are stored; a connection information storage unit in which one or more pieces of connection information for specifying connection between two or more somas are stored; an information transfer unit that acquires soma identifiers of one or more somas that accept information based on accepted input information; an output information acquiring unit that acquires output information, which is information that is output, using the information accepted by each soma identified with the one or more soma identifiers acquired by the information transfer unit; an information output unit that outputs the output information; and a growth unit that performs soma generation processing for generating soma-related information and accumulating the information in the soma-related information storage unit.

TECHNICAL FIELD

The present invention relates to an information processing apparatus andthe like capable of performing information processing for simulatinginformation processing in the brain.

BACKGROUND ART

Conventionally, there are brain wave signal processing apparatuses foracquiring and processing brain wave signals representing brain waves ofa subject (see Patent Documents 1 and 2, for example).

CITATION LIST Patent Documents

Patent Document 1: JP 2016-47239A

Patent Document 2: JP 2016-52430A

SUMMARY OF INVENTION Technical Problem

However, in conventional techniques, there is no information processingapparatus for simulating growth of cells and the like in the brain.

Solution to Problem

A first aspect of the present invention is directed to an informationprocessing apparatus including: a soma-related information storage unitin which two or more pieces of soma-related information having a somaidentifier for identifying a soma are stored; a connection informationstorage unit in which one or more pieces of connection information forspecifying connection between two or more somas are stored; an inputinformation accepting unit that accepts input information; aninformation transfer unit that acquires soma identifiers of one or moresomas that accept information based on the input information; an outputinformation acquiring unit that acquires output information, which isinformation that is output, using the information accepted by each somaidentified with the one or more soma identifiers acquired by theinformation transfer unit; an information output unit that outputs theoutput information acquired by the output information acquiring unit;and a growth unit that performs one or more of soma generationprocessing for generating soma-related information having a somaidentifier, and accumulating the information in the soma-relatedinformation storage unit, connection information generation processingfor generating connection information, and accumulating the informationin the connection information storage unit, and connection informationgrowth processing for growing connection information.

With this configuration, it is possible to realize an information.processing apparatus for simulating growth of cells and the like in thebrain.

Furthermore, a second aspect of the present invention is directed to theinformation processing apparatus according to the first aspect, whereinthe growth unit performs soma generation processing for generatingsoma-related information of a divided soma, which is a new soma obtainedby dividing a soma judged by a judging unit as a soma that has fired forthe number of times or at the frequency that is large enough to satisfya predetermined condition, and accumulating the information in thesoma-related information storage unit, and connection informationgeneration processing for generating connection information forconnecting a soma that satisfies the condition and a divided soma, andaccumulating the information in the connection information storage unit.

With this configuration, it is possible to realize an informationprocessing apparatus for simulating a growth method of cells and thelike in the brain.

Furthermore, a third aspect of the present invention is directed to theinformation processing apparatus according to the first or secondaspect, further including: a glial cell information storage unit inwhich one or more pieces of glial cell information having a somaidentifier for identifying a soma for connection, or a connectioninformation identifier for identifying connection information forconnection are stored, wherein the growth unit performs one or more ofsoma generation processing for generating soma-related information of adivided soma, which is a new soma obtained by dividing a soma connectedto glial cell information that satisfies a predetermined condition, andaccumulating the information in the soma-related information storageunit, and connection information growth processing for growing an axonor a dendrite connected to glial cell information that satisfies apredetermined condition.

With this configuration, it is possible to realize an informationprocessing apparatus for simulating a growth method of cells and thelike in the brain.

Furthermore, a fourth aspect of the present invention is directed to theinformation processing apparatus according to any one of the first tothird aspects, wherein the soma-related information has soma positionalinformation indicating a position of a soma, one or more pieces ofdendrite information, and one or more pieces of axon information, thedendrite information has a dendrite identifier and dendrite positionalinformation indicating a position of a dendrite, the axon informationhas an axon identifier and axon positional information indicating aposition of an axon, at least some of the one or more pieces ofconnection information in the connection information storage unit havean axon identifier of an axon of one soma and a dendrite identifier of adendrite of another soma, and the growth unit performs connectioninformation growth processing for changing the axon positionalinformation so as to allow an axon to extend or changing the dendritepositional information so as to allow a dendrite to extend, and, in acase in which axon positional information of an axon of one soma anddendrite positional information of a dendrite of another soma are closeto each other enough to satisfy a predetermined condition, performsconnection information generation processing for generating connectioninformation for specifying connection between the axon of the one somaand the dendrite of the other soma, and accumulating the information inthe connection information storage unit.

With this configuration, it is possible to realize an informationprocessing apparatus for simulating a growth method of cells and thelike in the brain.

Furthermore, a fifth aspect of the present invention is directed to theinformation processing apparatus according to the fourth aspect, whereinthe soma-related information has a soma group identifier for identifyinga soma group, which is a group to which a soma belongs, the informationprocessing apparatus further includes a soma group information storageunit in which two or more pieces of soma group information, each havinga soma group identifier for identifying a soma group and goalinformation for specifying a destination to which an axon or a dendriteconnected to a soma belonging to the soma group extends, are stored, andthe growth unit changes the axon positional information or the dendritepositional information such that an axon or a dendrite extends to adestination specified with the goal information contained in the somagroup information of a soma group to which a soma connected to the axonor the dendrite belongs.

With this configuration, it is possible to realize an informationprocessing apparatus for simulating a growth method of cells and thelike in the brain.

Furthermore, a sixth aspect of the present invention is directed to theinformation processing apparatus according to the third aspect, whereinthe glial cell information has glial cell positional information forspecifying a position of a glial cell, and the growth unit changes theaxon positional information of an axon identified with a connectioninformation identifier contained in the glial cell information, suchthat the position becomes closer to a position indicated by the glialcell positional information contained in the glial cell information.

With this configuration, it is possible to realize an informationprocessing apparatus for simulating a growth method of cells and thelike in the brain.

Furthermore, a seventh aspect of the present invention is directed tothe information processing apparatus according to any one of the firstto sixth aspects, further including: an apoptosis processing unit thatdeletes soma-related information from the soma-related informationstorage unit according to a predetermined condition.

With this configuration, it is possible to realize an informationprocessing apparatus for simulating apoptosis of cells and the like inthe brain.

Furthermore, an eighth aspect of the present invention is directed tothe information processing apparatus according to the seventh aspect,wherein, in a case in which the amount of soma-related informationstored in the soma-related information storage unit is large enough tosatisfy a predetermined condition, the apoptosis processing unit deletesthe soma-related information from the soma-related information storageunit.

With this configuration, it is possible to realize an informationprocessing apparatus for simulating an apoptosis method of cells and thelike in the brain.

Furthermore, a ninth aspect of the present invention is directed to theinformation processing apparatus according to the seventh or eighthaspect, further including: a firing information storage unit in whichone or more pieces of firing information having a soma identifier foridentifying a soma that has fired are stored; and a firing informationaccumulating unit that configures firing information having a somaidentifier for identifying a soma judged by the judging unit as a somathat fires, and accumulates the firing information in the firinginformation storage unit, wherein, using the one or more pieces offiring information in the firing information storage unit, the apoptosisprocessing unit determines a soma that is not connected to another soma,a dendrite, or an axon, determines a soma connected to an axon that doesnot reach a predetermined goal, or determines a soma that has fired forthe number of times that is small enough to satisfy a predeterminedcondition, and deletes soma-related information having a soma identifierof the determined soma, from the soma-related information storage unit.

With this configuration, it is possible to realize an informationprocessing apparatus for simulating an apoptosis method of cells and thelike in the brain.

Furthermore, a tenth aspect of the present invention is directed to theinformation processing apparatus according to any one of the first toninth aspects, wherein, in the soma-related information storage unit,firing condition information related to a condition for the soma to fireis also stored, the information processing apparatus further includes: afeature information acquiring unit that acquires one or more pieces offeature information from the input information, the information transferunit acquires the one or more pieces of feature information acquired bythe feature information acquiring unit and one or more soma identifierseach for identifying a soma that fires first, and acquires one or morepieces of feature information given from one or more other somas or oneor more pieces of feature information acquired from the one or morepieces of feature information, and a soma identifier of each of one ormore somas that are to be subjected to judgment of firing, theinformation processing apparatus further includes: a judging unit that,using the one or more pieces of feature information acquired by theinformation transfer unit, and firing condition information that ispaired with the one or more sonata identifiers acquired by theinformation transfer unit, judges whether or not the soma identifiedwith each of the soma identifiers fires; and a firing pattern acquiringunit that acquires a firing pattern containing one or more somaidentifiers each for identifying a soma judged by the judging unit as asoma that fires, the output information acquiring unit acquires, fromthe output management information storage unit, output informationcorresponding to the firing pattern acquired by the firing patternacquiring unit, the information transfer unit acquires the somaidentifier of each of the one or more somas connected to the soma judgedby the judging unit as a soma that fires, using the one or more piecesof feature information applied to soma-related information of the somajudged by the judging unit as a soma that fires or one or more pieces offeature information acquired from the one or more pieces of featureinformation, and the connection information in the connectioninformation storage unit, and the processing by the judging unit, theprocessing by the firing pattern acquiring unit, and the processing bythe information transfer unit are repeated twice or more.

With this configuration, it is possible to realize an informationprocessing apparatus for simulating processing in the brain.

Furthermore, an eleventh aspect of the present invention is directed tothe information processing apparatus according to the tenth aspect,wherein, in the output management information storage unit, one or morepieces of output management information having an output condition,which is a condition using a firing pattern having one or more sonataidentifiers and information related to one or more pieces of additionalinformation that is additional information, and output information,which is information that is output, are stored, the input informationaccepting unit accepts one or more pieces of additional information, andthe output information acquiring unit determines an output conditionthat matches the one or more soma identifiers acquired by the firingpattern acquiring unit and the one or more pieces of additionalinformation accepted by the input information accepting unit, andacquires output information that is paired with the output condition.

With this configuration, it is possible to realize an informationprocessing apparatus for simulating processing in the brain in which theoutput varies even with the same input, depending on additionalinformation.

Furthermore, a twelfth aspect of the present invention is directed tothe information processing apparatus according to any one of the firstto eleventh aspects, wherein the output information contains any ofemotion information related to emotion of a person, intentioninformation indicating intention of a person, and behavior informationrelated to body movements of a person.

With this configuration, it is possible to simulate processing in thebrain, to output emotion and intention, and to express behaviors.

Advantageous Effects of Invention

With the information processing apparatus according to the presentinvention, it is possible to realize an information processing apparatusfor simulating growth of cells and the like in the brain.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram of an information processing apparatus A inEmbodiment 1.

FIG. 2 is a block diagram of a processing unit 3 constituting theinformation processing apparatus A in the embodiment.

FIG. 3 is a flowchart illustrating an operation example of theinformation processing apparatus A in the embodiment.

FIG. 4 is a flowchart illustrating an example of firing transferprocessing in the embodiment.

FIG. 5 is a flowchart illustrating an example of firing judgmentprocessing in the embodiment.

FIG. 6 is a flowchart illustrating the details of an example of firingpattern processing in the embodiment.

FIG. 7 is a flowchart illustrating an example of soma growth processingin the embodiment.

FIG. 8 is a flowchart illustrating an example of axon growth processingin the embodiment.

FIG. 9 is a flowchart illustrating an example of dendrite growthprocessing in the embodiment.

FIG. 10 is a flowchart illustrating an example of soma connectionprocessing in the embodiment.

FIG. 11 is a flowchart illustrating an example of glial cell growthprocessing in the embodiment,

FIG. 12 is a flowchart illustrating an example of apoptosis processingin the embodiment.

FIG. 13 is a block diagram of a first example of an informationprocessing apparatus B in Embodiment 2.

FIG. 14 is a block diagram of a second example of the informationprocessing apparatus B in Embodiment 2.

FIG. 15 is a flowchart illustrating an operation example of theinformation processing apparatus B in the embodiment,

FIG. 16 is a flowchart illustrating an example of transfer outputprocessing in the embodiment.

FIG. 17 is a schematic view of a computer system in the embodiment.

FIG. 18 is a block diagram of the computer system in the embodiment.

DESCRIPTION OF EMBODIMENT

Hereinafter, an embodiment of an information processing apparatus andthe like will be described with reference to the drawings. It should benoted that constituent elements denoted by the same reference numeralsin the embodiments perform similar operations, and thus a descriptionthereof may not be repeated.

Embodiment 1

In this embodiment, an information processing apparatus will bedescribed in which a firing condition of one or more somas (which may bereferred to as nerve cell bodies) is stored, and the informationprocessing apparatus judges whether or not each soma fires, using one ormore pieces of information obtained from input, acquires a firingpattern from a judgment result, and determines and outputs outputinformation using the firing pattern.

Furthermore, in this embodiment, an information processing apparatuswill be described in which feature information transfer processing isperformed using firing start point information for managing informationindicating a soma that fires first, according to feature information.

Furthermore, in this embodiment, an information processing apparatuswill be described in which calculation processing on two or more piecesof feature information transferred via two or more links to a soma isperformed in the soma,

Furthermore, in this embodiment, an information processing apparatuswill be described in which there are two or more soma groups (which maybe referred to as nerve cell body groups), and information is deliveredbetween soma groups that are connected to each other.

Furthermore, in this embodiment, an information processing apparatuswill be described in which information delivery is performed such thatinformation is delivered or is not delivered via a link having an axon(which may be referred to a nerve fiber) and a dendrite (which may bereferred to a branched extension).

Furthermore, in this embodiment, an information processing apparatuswill be described in which information transfer is performed alsoconsidering synapses and spines.

Furthermore, in this embodiment, an information processing apparatuswill be described in which an element that has operated does not operateas long as the length of time that has elapsed is not long enough tosatisfy a predetermined condition. The element is, for example, soma, anaxon, or a dendrite.

Furthermore, in this embodiment, an information processing apparatuswill be described in which a firing probability of a soma that has firedis increased.

Furthermore, in this embodiment, an information processing apparatuswill be described in which different pieces of output information areoutput depending on a firing pattern and one or more pieces of externalinformation. The external information is, for example, weather,temperature, scenery in the outside world, odor, a sound, light, or thelike.

Furthermore, in this embodiment, an information processing apparatuswill be described that has a learning function.

Furthermore, in this embodiment, an information processing apparatuswill be described in which an element automatically grows. A trigger forthe growth is firing, accepting information, or the like.

Furthermore, in this embodiment, an information processing apparatuswill be described that has glial cell information, wherein the glialcell information affects growth.

Furthermore, in this embodiment, an information processing apparatuswill be described in which elements have positional information, andgrowth and connection of the elements are realized using the positionalinformation.

Furthermore, in this embodiment, an information processing apparatuswill be described that simulates how an axon and the like actually grow.

Moreover, in this embodiment, an information processing apparatus willbe described that simulates apoptosis processing of cells such as somas.In this example, for example, if the number of somas is large enough tosatisfy a predetermined condition, somas are deleted, somas that firefor the number of times that is small enough to satisfy a predeterminedcondition are deleted, somas that are not connected to a dendrite or anaxon are deleted, or somas that are connected to an axon that does notreach a predetermined goal are deleted.

FIG. 1 is a block diagram of an information processing apparatus A inthis embodiment. The information processing apparatus A includes astorage unit 1, an accepting unit 2, a processing unit 3, and an outputunit 5. FIG. 2 is a block diagram of the processing unit 3 constitutingthe information processing apparatus A.

The storage unit 1 includes a sonata-related information storage unit11, a soma group information storage unit 12, a connection informationstorage unit 13, a glial cell information storage unit 14, a firingstart point information storage unit 15, an output managementinformation storage unit 16, a learning condition storage unit 17, alearning information storage unit 18, a firing information storage unit19, and a used connection information storage unit 20.

The accepting unit 2 includes an input information accepting unit 21.

The processing unit 3 includes a feature information acquiring unit 31,an information transfer unit 32, a soma calculating unit 33, a judgingunit 34, a firing probability changing unit 35, a firing patternacquiring unit 36, an output information acquiring unit 37, a controlunit 38, a learning detecting unit 39, a learning informationaccumulating unit 40, a growth unit 41, an apoptosis processing unit 42,and a firing information accumulating unit 43.

The information transfer unit 32 includes a firing start point somadetermining part 321, a connection detecting part 322, and a transferinformation acquiring part 323.

The output unit 5 includes an information output unit 51.

In the storage unit 1, various types of information are stored. Thevarious types of information are, for example, later-describedsoma-related information, later-described soma group information,later-described connection information, later-described glial cellinformation, later-described firing start point information,later-described output management information, a later-describedlearning condition, later-described learning information,later-described firing information, and later-described used connectioninformation.

In the soma-related information storage unit 11, two or more pieces ofsoma-related information are stored.

The soma-related information is information related to a soma. Thesoma-related information has a soma identifier and firing conditioninformation. The soma-related information typically has one or morepieces of dendrite information and one or more pieces of axoninformation. The dendrite information is information related to adendrite that realizes information input to a soma. The dendriteinformation has a dendrite identifier. The dendrite identifier isinformation for identifying a dendrite, and is, for example, an ID, aname, or the like. The dendrite information preferably has dendritepositional information. The axon information is information related toan axon that realizes information output from a soma. The axoninformation has an axon identifier. The axon identifier is informationfor identifying an axon, and is, for example, ID, a name or the like.The axon information preferably has axon positional information. Thesoma-related information may have goal information. The goal informationis information for specifying a goal. The goal is a destination to whichan axon or a dendrite connected to a soma extends. The goal informationis information indicating a position. The goal information is, forexample, positional information. The goal information is, for example,three-dimensional coordinates (x, y z), two-dimensional coordinates (x,y), or four-dimensional quaternions (x, y x, w).

Note that, when connection between somas is represented by informationof one link, the soma-related information may not have the dendriteinformation or the axon information,

Furthermore, the soma-related information may have a synapse identifierfor identifying a synapse or a spine identifier for identifying a spine,in association with the axon information or the dendrite information.The synapse identifier is typically in association with the axoninformation. Also, the spine identifier is typically in association withthe dendrite information.

Furthermore, the soma-related information may have a soma groupidentifier for identifying a soma group, which is a group to which asoma belongs. The soma-related information may be in association withthe soma group identifier.

Furthermore, the soma-related information preferably has soma positionalinformation indicating a position of a soma. The soma positionalinformation is, for example, three-dimensional coordinates (x, ytwo-dimensional coordinates (x, y), or four-dimensional quaternions (x,x, w).

Furthermore, the dendrite positional information is information forspecifying a position of a dendrite, and is, for example, one or atleast two sets of three-dimensional coordinates (x, y, z), or one or atleast two sets of two-dimensional coordinates (x, y). If the dendritepositional information has two or more sets of coordinates, the dendriteis a line obtained by linking points represented by the two or more setsof coordinates.

Furthermore, the axon positional information is information forspecifying a position of an axon, and is, for example, one or at leasttwo sets of three-dimensional coordinates (x, y z), or one or at leasttwo sets of two-dimensional coordinates (x, y). If the axon positionalinformation has two or more sets of coordinates, the axon is a lineobtained by linking points represented by the two or more sets ofcoordinates.

Note that a dendrite and an axon may be branched. If a dendrite and anaxon are branched, the positional information thereof can be representedby three or at least four set of coordinates. There is no limitation onthe method for representing the dendrite positional information and theaxon positional information.

Furthermore, the soma identifier is information for identifying a soma.The soma identifier is, for example, an ID, a name, or the like. Thefiring condition information is information related to a condition forthe soma to fire. The firing condition information typically has one ormore pieces of feature information. The feature information may beinformation having an information identifier for identifying informationand an information amount indicating a magnitude of information, or maybe information only having an information amount indicating a magnitudeof information. The information amount is, for example, a numeric valuegreater than 0. The firing condition information is, for example,“feature information≥0.5”, “feature information>0.7”, “informationamount≥0.5”, “information amount>0.7”, “(information identifier=A &information amount≥0.5) & (information identifier=B & informationamount>0.8)”, or the like. The feature information constituting thefiring condition information is an information amount. The featureinformation is, for example, a feature amount, but also may be inputinformation itself. The feature amount is, for example, a feature amountof an image obtained as a result of image analysis, or a feature amountof a speech obtained as a result of speech analysis. The firingcondition information preferably has firing probability information. Thefiring probability information is information related to a probabilityof firing. The firing probability information may be a firingprobability itself, or may be a value or the like obtained by convertingthe firing probability through a function or the like. It is preferablethat the firing probability information is referred to, and, dependingon the probability indicated by the firing probability information, asoma may fire or may not fire even at the same feature information.

Two or more pieces of soma-related information may be grouped. The term“grouped” is, for example, a state in which a soma group identifier isassociated with pieces of soma-related information. The state of beingassociated is a concept that they can be associated with each other. Thesoma group identifier is information for identifying a soma group, whichis a group to which a soma belongs. The term “grouped” is a state inwhich, for example, pieces of soma-related information have the samegoal information. The term “grouped” is, for example, a state of havingthe same soma group identifier, or is, for example, a state in whichpieces of soma-related information in a group are connected to eachother via a link. It will be appreciated that there is no limitation onthe method for grouping soma-related information and the data structure.The soma-related information may have a soma group identifier.

Furthermore, the soma-related information preferably has held energyamount information indicating the amount of energy held by a soma. Thesoma-related information preferably has necessary energy amountinformation indicating the amount of energy necessary for firing. Thedendrite information preferably has held energy amount informationindicating the amount of energy held by a dendrite. The dendriteinformation preferably has necessary energy amount informationindicating the amount of energy necessary to perform informationtransfer using a dendrite. The axon information preferably has heldenergy amount information indicating the amount of energy held by anaxon. The axon information preferably has necessary energy amountinformation indicating the amount of energy necessary to performinformation transfer using an axon.

In the soma group information storage unit 12, two or more pieces ofsoma group information are stored. The soma group information has a somagroup identifier and goal information. The goal information isinformation for specifying a destination to which an axon or a dendriteconnected to a soma belonging to a soma group extends. The goalinformation is, for example, one or at least two sets ofthree-dimensional coordinates (x, y, z) or one or at least two sets oftwo-dimensional coordinates (x, y). The goal information may be, forexample, information indicating a direction.

In the connection information storage unit 13, one or at least twopieces of connection information are stored. The connection informationis information for specifying connection between two or more somas. Theconnection information may be information for specifying connectionbetween an axon of one soma and a dendrite of another soma. Thisinformation is also information for specifying connection between somas.The connection information may be information for specifying connectionbetween one synapse and one spine. This information is also informationfor specifying connection between somas. The connection information has,for example, two soma identifiers of somas that are connected to eachother. The connection information has, for example, an axon identifierof an axon, and a dendrite identifier of a dendrite that is connected tothe axon. The connection information has, for example, a synapseidentifier of a synapse, and a spine identifier of a spine that canperform information transfer with the synapse. The connectioninformation may have information transfer probability information. Theinformation transfer probability information is information related to aprobability at which information transfer between one soma and anothersoma is performed. The information transfer probability information maybe information related to a probability at which information transferbetween an axon and a dendrite is performed. Also in this case, theinformation transfer probability information is information related to aprobability at which information transfer between one soma and anothersoma is performed. The information transfer probability information maybe information related to a probability at which information transferbetween a synapse and a spine is performed. Also in this case, theinformation transfer probability information is information related to aprobability at which information transfer between one soma and anothersoma is performed. In this example, the connection direction betweensomas is typically one direction.

The connection information may be information indicating connectionbetween a soma and an axon. In this case, the connection information hasa soma identifier and an axon identifier. The connection information maybe information indicating connection between a soma and a dendrite. Inthis case, the connection information has a soma identifier and adendrite identifier.

The connection information may be information for specifying connectionbetween a glial cell and an axon or a dendrite. In this case, theconnection information has, for example, a glial cell identifier foridentifying glial cell information and an axon identifier. Theconnection information may have, for example, a glial cell identifierand a dendrite identifier.

In the glial cell information storage unit 14, one or at least twopieces of glial cell information are stored. The glial cell informationis information related to a glial cell. The glial cell informationpreferably has a glial cell identifier for identifying a glial cell. Theglial cell information has, for example, a soma identifier foridentifying a soma that supports connection, or a connection informationidentifier for identifying connection information that supportsconnection. The glial cell information has, for example, an axonidentifier of an axon whose connection is supported by the glial cell,or a dendrite identifier of a dendrite whose connection is supported bythe glial cell. The glial cell information preferably has a glial celltype identifier for identifying the type of glial cell. The type ofglial cell is, for example, an oligodendrocyte (hereinafter referred toas “oligo” as appropriate), or an astrocyte. An oligo is a cell that canbe connected to an axon. An astrocyte is a cell that can be connected toa soma or a dendrite. The glial cell information preferably has glialcell positional information for specifying a position of a glial cell.In particular, the glial cell information of an oligo preferably has theglial cell positional information. The glial cell information may haveprojection length information indicating a length of each of one or moreprojections. The glial cell information may have projection numberinformation indicating the number of projections projecting from a glialcell. Typically, it is preferable that, when the length of the entireglial cell calculated from the projection length information of eachprojection reaches a threshold value, the glial cell does not grow anymore.

In the firing start point information storage unit 15, one or morepieces of firing start point information are stored. The firing startpoint information has an information identifier for identifying featureinformation, and one or more soma identifiers each for identifying asoma that fires when the feature information is accepted. Theinformation identifier is, for example, information for specifying thetype of feature amount of an image, and is, for example, red “R”composing a color, green “G” composing a color, and blue “B” composing acolor. The information identifier is, for example, information forspecifying the type of feature amount of a sound, and is, for example,“frequency”, “amplitude”, or the like.

In the output management information storage unit 16, one or at leasttwo pieces of output management information are stored. The outputmanagement information is information having an output condition andoutput information. The output management information may be informationof a pair of an output condition and output information,

The output condition is a condition that is used to determine outputinformation. The output condition is a condition for output using thefiring pattern. The output condition may be a firing pattern itself, ormay be information having a firing pattern and output probabilityinformation. The output probability information is information relatedto a probability for acquiring output information. The output conditionmay be a firing pattern, and information of the lower limit of thenumber of soma identifiers contained in the firing pattern that isapplied, or may be a firing pattern, and information of the lower limitof the proportion of soma identifiers contained in the firing patternthat is applied, for example. The firing pattern has one or more somaidentifiers. The firing pattern is a pattern of firing of one or atleast two somas. The output information is information corresponding tothe firing pattern. The output information is, for example, emotioninformation related to emotion of a person, intention informationindicating intention of a person, behavior information related to bodymovements of a person, or the like. The emotion information is, forexample, joy sadness, a frightened feeling, a surprised feeling, or thelike. The emotion information is, for example, an ID for identifyingemotion. The intention information is, for example, information foridentifying intention. The behavior information is, for example,information that is reflected in a behavior of an avatar (character).The technique for moving an avatar is a known technique, and thus adetailed description thereof has been omitted.

The output condition may be a condition using information related to afiring pattern and one or more pieces of external information. Theexternal information is information of external conditions. The externalinformation may be referred to as a user context. The externalinformation is, for example, temperature, weather, an odor, a sound,light, or the like. The external information is typically informationthat is accepted when input information is accepted, and that is otherthan the input information.

In the learning condition storage unit 17, one or at least two learningconditions are stored. Each learning condition is a condition forperforming learning. The learning condition is a condition using thefiring pattern. The learning condition may be a firing pattern itself.The learning condition may be, for example, a firing pattern having oneor more soma identifiers, and the number of somas that have to fire inorder to perform learning or the proportion of somas that have to firein order to perform learning (the number of somas that fire among thesoma identifiers contained in the firing pattern contained in thelearning condition/the number of soma identifiers contained in thefiring pattern contained in the learning condition), or the like. Thelearning condition may have a firing pattern and learning probabilityinformation. The learning probability information is information relatedto a probability at which it is determined to perform learning. If thelearning condition has learning probability information, there is thecase in which it is probabilistically judged “not to perform learning”using the learning probability information even in the case in which itcan be judged “to perform learning” using the firing pattern.

In the learning information storage unit 18, one or at least two piecesof learning information are stored. The learning information isinformation obtained through learning. The learning information isinformation that is used after learning. The learning information hasinput information or one or more pieces of feature information acquiredfrom the input information, and a firing pattern. In this example, thefeature information may be an information identifier for identifyingfeature information. In this example, the feature information may be aninformation identifier and an information amount. The learninginformation may have holding time information indicating a holding timeof a firing pattern. The holding time is a period of time if for whichthe firing pattern is not used, the firing pattern is deleted. Theprocessing for deleting learning information if the learning informationis not used for the time indicated by the holding time information isperformed, for example, by the processing unit 3.

In the firing information storage unit 19, one or at least two pieces offiring information are stored. In this example, the firing informationis information related to a result of firing. The firing information hasa soma identifier for identifying a soma that has fired. The firinginformation may typically have tinier information indicating the time atwhich firing occurred. The timer information may be informationindicating a relative time, or may be information indicating an absolutetime. The firing information in the firing information storage unit 19may be automatically deleted by the processing unit 3 after the elapseof a predetermined period of time after the firing information wasaccumulated.

In the used connection information storage unit 20, one or at least twopieces of used connection information are stored. The used connectioninformation is information indicating a history in which connectioninformation was used for information transfer. The used connectioninformation may be information indicating a history in which an axon ora dendrite was used for information transfer. The used connectioninformation has, for example, a connection information identifier. Theused connection information has, for example, an axon identifier and/ora dendrite identifier. The used connection information has, for example,a synapse identifier and/or a spine identifier. The used connectioninformation may have, for example, timer information indicating the timeat which connection information was used.

The accepting unit 2 accepts various types of information. The varioustypes of information are, for example, later-described inputinformation, external information, or the like. The various types ofinformation may be input by any part such as a camera, a microphone, anumeric keypad, a keyboard, a mouse, a menu screen, or various types ofsensors such as a motion sensor or a temperature sensor. The acceptingunit 2 may be realized by a device driver for an input part such as acamera, a microphone, a numeric keypad, or a keyboard, control softwarefor a menu screen, or the like. The accepting is a concept thatencompasses accepting information input from an input device such as acamera, a microphone, a keyboard, a mouse, or a touch panel, receivinginformation transmitted via a wired or wireless communication line, andaccepting information read from a storage medium such as an opticaldisk, a magnetic disk, a semiconductor memory or the like.

The input information accepting unit 21 accepts input information. Theinput information is information that is input. The input informationis, for example, a moving image, a still image, a speech, a characterstring, or the like. There is no limitation on the data type, datastructure, and the like of the input information. It is preferable thatthe input information accepting unit 21 also accepts one or more piecesof external information.

The processing unit 3 performs various types of processing. The varioustypes of processing are, for example, processes that are performed bythe feature information acquiring unit 31, the information transfer unit32, the soma calculating unit 33, the judging unit 34, the firingprobability changing unit 35, the firing pattern acquiring unit 36, theoutput information acquiring unit 37, the control unit 38, the learningdetecting unit 39, the learning information accumulating unit 40, thegrowth unit 41, the apoptosis processing unit 42, the firing informationaccumulating unit 43, and the like.

The feature information acquiring unit 31 acquires one or more pieces offeature information from the input information. The feature informationis, for example, a feature amount, input information itself or the like.The feature information has, for example, an information identifier andan information amount.

For example, the feature information acquiring unit 31 performs imageanalysis on input information, which is an accepted image, therebyacquiring a pair of one or more pieces of information identifier and aninformation amount of the image. For example, the feature informationacquiring unit 31 performs image analysis on input information, which isan accepted image, thereby acquiring three pairs of informationconsisting of “information identifier “R” (indicating red) andinformation amount=521”, “information identifier “CG” (indicating green)and information amount=219”, and “information identifier “B” (indicatingblue) and information amount=56”. This information is informationindicating values of R, G, and B.

For example, the feature information acquiring unit 31 analyzes inputinformation, which is an accepted speech, thereby acquiring one or morepieces of feature information of the speech. For example, the featureinformation acquiring unit 31 analyzes input information, which is anaccepted speech, thereby acquiring “information identifier (frequency=X)and information amount=50”, “information identifier (frequency=Y) andinformation amount=120”, and the like. This information is informationindicating levels at the respective frequencies.

Note that the processing for acquiring a feature amount of an image andthe processing for acquiring a feature amount of a speech are knowntechniques, and thus a detailed description thereof has been omitted.

The information transfer unit 32 acquires the one or more pieces offeature information acquired by the feature information acquiring unit31 and one or more soma identifiers each for identifying a soma thatfires first. The information transfer unit 32 acquires, from the firingstart point information storage unit 15, one or more soma identifiersthat are each paired with an information identifier contained in thefeature information acquired by the feature information acquiring unit31, and acquires, as a pair, each of the one or more soma identifiersand an information amount contained in the feature information acquiredby the feature information acquiring unit 31. Typically, an informationamount is given to each of the somas identified with the one or moresoma identifiers. The somas identified with the one or more somaidentifiers may be an identifier of a soma that fires first.

The information transfer unit 32 acquires one or more pieces of featureinformation given from one or more other somas or one or more pieces offeature information acquired from the one or more pieces of featureinformation, and a soma identifier of each of one or more somas that areto be subjected to judgment of firing.

The information transfer unit 32 acquires one or more pieces of featureinformation applied to the soma-related information of a soma judged bythe judging unit 34 as a soma that fires or one or more pieces offeature information acquired from the one or more pieces of featureinformation, and a soma identifier of each of the one or more somasconnected to the soma judged by the judging unit 34 as a soma thatfires. The information transfer unit 32 acquires a soma identifier ofeach of the one or more somas connected to the soma judged by thejudging unit 34 as a soma that fires, using the connection informationin the connection information storage unit 13.

The information transfer unit 32 acquires one piece of featureinformation acquired by a later-described soma calculating unit 33, anda soma identifier of each of one or more somas that are to be subjectedto judgment of firing in this example, the one piece of featureinformation is typically one information amount.

There is the case in which, using the connection information forspecifying connection between a soma group containing a soma judged bythe judging unit 34 as a soma that fires (referred to as a first somagroup) and another soma group (referred to as a second soma group), theinformation transfer unit 32 acquires soma identifiers of one or moresomas contained in the second soma group. The soma identifiers of one ormore somas contained in the second soma group are identifiers of somasthat are positioned close to the first soma group.

The information transfer unit 32 probabilistically acquires a somaidentifier of each of the one or more somas connected to the soma judgedby the judging unit 34 as a soma that fires, using the informationtransfer probability information contained in the connection informationin the connection information storage unit 13. The probabilisticallyacquiring is either judging that a soma fires or judging that the somadoes not fire, depending on information of probability (informationtransfer probability information, in this example). The processing forthe probabilistically acquiring is a known technique, and thus adetailed description thereof has been omitted.

Note that, it is preferable that, for example, based on used connectioninformation indicating a history in which, an axon, a dendrite, asynapse, or a spine was used, the information transfer unit 32 performsinformation transfer to a next soma only if the later-described judgingunit 34 judges that at least a predetermined period of time has elapsedafter the axon, the dendrite, the synapse, or the spine was recentlyused, or judges that they have not been used for a period of timegreater than the predetermined period of time.

Furthermore, in the case of performing information transfer to a nextsoma, the information transfer unit 32 preferably configures usedconnection information, and accumulates it in the used connectioninformation storage unit 20. That is to say, in the case of performinginformation transfer to a next soma, the information transfer unit 32acquires timer information indicating the current time from an unshowntimer. The information transfer unit 32 acquires one or more of the axonidentifier of the used axon, the dendrite identifier of the useddendrite, the synapse identifier of the used synapse, or the spineidentifier of the used spine. The information transfer unit 32configures used connection information having the timer information andthe acquired one or more identifiers, and accumulates it in the usedconnection information storage unit 20. Alternatively for example, theinformation transfer unit 32 acquires a connection informationidentifier of connection (link) used for the information transfer,acquires timer information indicating the current time from an unshowntinier, configures used connection information having the connectioninformation identifier and the timer information, and accumulates it inthe used connection information storage unit 20.

Furthermore, it is preferable that, in the case of performinginformation transfer to a next soma, the information transfer unit 32reduces the energy amount indicated by the held energy amountinformation that is paired with the axon identifier of the axon used forthe transfer and the held energy amount information that is paired withthe dendrite identifier of the dendrite used for the transfer. It isassumed that the function for reducing the energy amount is stored, forexample, in the storage unit 1. There is no limitation on the function.The function is, for example, Numerical Formula. 1 below.

$\begin{matrix}{{f(t)} = {{{u(t)}{{Vs}\left( {1 - e^{- {({t/\tau})}}} \right)}} + {{u(t)}{E\left( e^{- {({t/\tau})}} \right)}}}} & {{Numerical}\mspace{14mu} {Formula}\mspace{14mu} 1} \\{{u(t)} = \left\{ \begin{matrix}{= 0} & {t \leq 0} \\{= 1} & {t > 0^{\prime}}\end{matrix} \right.} & \; \\{{{Vs} = {E + {\frac{1}{g}I}}},\mspace{14mu} {\tau = {c/g}}} & \;\end{matrix}$

In Numerical Formula 1, E, g, and c are parameters, and I is an inputsignal (request signal). In Numerical Formula 1, for example, E=−65 mV,g=0.025 μS, and C=0.5 nF.

The firing start point soma determining part 321 acquires one or moresoma identifiers that are respectively paired with informationidentifiers for identifying the one or more pieces of featureinformation acquired by the feature information acquiring unit 31, fromthe firing start point information storage unit 15. The informationidentifiers may be contained in the feature information acquired by thefeature information acquiring unit 31, or may be associated with thefeature information or the information amount acquired by the featureinformation acquiring unit 31.

The connection detecting part 322 detects one or more somas connected toa soma judged by the judging unit 34 as a soma that fires, using theconnection information in the connection information storage unit 13.The detecting a soma is typically acquiring a soma identifier.

For example, the connection detecting part 322 acquires a somaidentifier of a soma judged by the judging unit 34 as a soma that fires,and acquires one or more soma identifiers that are each paired with thesoma identifier, from the connection information storage unit 13.

For example, the connection detecting part 322 acquires a somaidentifier of a soma judged by the judging unit 34 as a soma that fires,acquires an axon identifier that is paired with the soma identifier,from the soma-related information storage unit 11, acquires a dendriteidentifier that is paired with the axon identifier, from the connectioninformation storage unit 13, and acquires a soma identifier that ispaired with the dendrite identifier, from the soma-related informationstorage unit 11.

For example, the connection detecting part 322 acquires a somaidentifier of a soma judged by the judging unit 34 as a soma that fires,acquires a synapse identifier that is paired with the soma identifier,from the soma-related information storage unit 11, acquires a spineidentifier that is paired with the synapse identifier, from theconnection information storage unit 13, and acquires a soma identifierthat is paired with the spine identifier, from the soma-relatedinformation storage unit 11.

For example, the connection detecting part 322 acquires a soma groupidentifier of a soma group to which a soma judged by the judging unit 34as a soma that fires belongs. If the soma judged by the judging unit 34as a soma that fires is a soma at an end in the soma group (does nothave any other soma to which the soma transfers the feature information,in the same soma group), the connection detecting part 322 acquires asoma group identifier of another soma group that is paired with the somagroup identifier for identifying the soma group, from the connectioninformation storage unit 13. Next, for example, the connection detectingpart 322 acquires one or more soma identifiers for identifying one ormore somas at an end in the soma group specified with the acquired somagroup identifier (somas that do not receive feature information fromanother soma in the same soma group).

For example, if the soma identifier of the soma judged by the judgingunit 34 as a soma that fires is stored in the storage unit 1 as the lastsoma of the information transfer in the soma group to which the somabelongs, the connection detecting part 322 acquires a soma groupidentifier of another soma group that is paired with the soma groupidentifier for identifying the soma group, from the connectioninformation storage unit 13. For example, if a soma is stored in thestorage unit 1 as a soma that first receives information transfer fromanother soma group, among somas with one or more soma identifiers thatare each paired with the acquired soma group identifier of the othersoma group, the connection detecting part 322 acquires a soma identifierof the soma from the storage unit 1.

The transfer information acquiring part 323 acquires information that isused for information transfer between somas. The transfer informationacquiring part 323 acquires feature information that is transferred anda soma identifier of a soma that is a transfer destination. The transferinformation acquiring part 323 acquires, for example, one or more piecesof feature information applied to the soma-related information of a somajudged by the judging unit 34 as a soma that fires or one or more piecesof feature information acquired from the one or more pieces of featureinformation, and soma identifiers of one or more somas detected by theconnection detecting part 322.

The soma calculating unit 33 performs calculation on two or more piecesof feature information given from two or more other somas, therebyacquiring one piece of feature information. In this example, the featureinformation is typically an information amount. That is to say, the somacalculating unit 33 typically performs calculation on two or moreinformation amounts given from two or more other somas, therebyacquiring one information amount. The calculation is predeterminedcalculation. The calculation is, for example, a process that adds two ormore information amounts given from two or more other somas. Thecalculation is, for example, a process that adds two or more informationamounts given from two or more other somas, and then multiplies theobtained result by a constant that is less than 1.

Using the one or more pieces of feature information acquired by theinformation transfer unit 32, and firing condition information that ispaired with the one or more soma identifiers acquired by the informationtransfer unit 32, the judging unit 34 judges whether or not the somaidentified with each of the soma identifiers fires. The one or morepieces of feature information are, for example, information amounts.

The judging unit 34 acquires, for example, firing condition informationthat is paired with each of the one or more soma identifiers acquired bythe information transfer unit 32, from the soma-related informationstorage unit 11 The judging unit 34 judges, for example, whether or notthe information amount acquired by the information transfer unit 32matches the condition indicated by the acquired firing conditioninformation.

It is preferable that the judging unit 34 does not judge that a soma,judged as a soma that has fired, fires, as long as the length of timethat has elapsed is not long enough to satisfy a predeterminedcondition. The not judging that a soma fires may be judging that a somadoes not fire.

The judging unit 34 acquires recent timer information, the timerinformation being paired with a soma identifier of a soma that is to besubjected to judgment, for example, referring to the firing informationstorage unit 19. The judging unit 34 acquires current timer information,for example, from an unshown timer. The judging unit 34 acquiresinformation of the time elapsed after the recent firing, for example,from the current tinier information and the recent timer information.Next, it is preferable that the judging unit 34 judges whether or notthe elapsed time is less than a threshold value or is less than or equalto a threshold value, and, if it is judged that the elapsed time is lessthan a threshold value or is less than or equal to a threshold value,the judging unit 34 judges that the soma does not fire.

If the firing condition information has firing probability informationindicating a firing probability the judging unit 34 judges whether ornot a soma fires, using the firing probability information, and thus thejudging unit 34 either judges that a soma fires or judges that the somadoes not fire, in the case of judging whether or not the soma fires evenusing the same one or more pieces of feature information and the samefiring condition information. That is to say, it is preferable that,even in the case in which the same one or more pieces of featureinformation are given to one soma, the judging unit 34 either judgesthat the soma fires or judges that the soma does not fire, depending onthe firing probability information corresponding to the soma.

Furthermore, it is preferable that, even in the case in which the sameone or more pieces of feature information are input, the judging unit 34either judges that a soma fires or judges that the soma does not fire,depending on external information.

The judging unit 34 accumulates, for example, a soma identifier of asoma that has fired and timer information indicating the time at whichfiring occurred, as a pair, in the storage unit 1. That is to say, if itis judged that a soma has fired, the judging unit 34 acquires timerinformation from an unshown timer. Then, the judging unit 34 accumulatesfiring information having a soma identifier of the soma that has firedand the timer information, in the firing information storage unit 19.

It is also preferable that, if an operation regarding the connectioninformation has been performed once, the operation is not performed aslong as the length of time that has elapsed is not long enough tosatisfy a predetermined condition. That is to say, it is preferable thatthe judging unit 34 acquires timer information indicating the time atwhich an axon, a dendrite, a synapse, or a spine that is used forinformation transfer was recently used, from the used connectioninformation storage unit 20, compares it with the timer informationindicating the current time, and judges not to perform informationtransfer using the axon, the dendrite, the synapse, or the spine as longas the length of time that has elapsed is not long enough to satisfy apredetermined condition.

Furthermore, it is preferable that, if it is judged that one soma fires,the judging unit 34 reduces the energy amount indicated by the heldenergy amount information contained in the soma-related information ofthe soma. It is assumed that the function for reducing the energy amountis stored, for example, in the storage unit 1. There is no limitation onthe function. The function is, for example, Numerical Formula 2 below.

$\begin{matrix}{{f(t)} = {\frac{\sin^{2}{Nt}}{\sin^{2}t}\left( {{N = 1},2,3,\ldots}\mspace{14mu} \right)}} & {{Numerical}\mspace{14mu} {Formula}\mspace{14mu} 2}\end{matrix}$

In Numerical Formula 2, t is the time, and f(t) is the amount of energyheld.

The firing probability changing unit 35 changes the firing probabilityinformation corresponding to a soma judged by the judging unit 34 as asoma that fires, so as to increase the firing probability. That is tosay the firing probability changing unit 35 acquires a soma identifierof a soma judged by the judging unit 34 as a soma that fires, andchanges the firing probability information that is paired with the somaidentifier, so as to increase the firing probability. There is nolimitation on the algorithm for changing the firing probabilityinformation. The firing probability changing unit 35 may add apredetermined value to the firing probability information, may add apredetermined proportion of value to the firing probability information,or may acquire an increasing probability based on accepted one or morepieces of feature information, for example. That is to say, the degreeof increase in the probability may be constant, or may be dynamicallychanged.

The firing pattern acquiring unit 36 acquires a firing patterncontaining one or more soma identifiers each for identifying a somajudged by the judging unit 34 as a soma that has fired.

It is preferable that the firing pattern acquiring unit 36 applies theinput information accepted by the input information accepting unit 21 orone or more pieces of feature information acquired from the inputinformation to one or more pieces of learning information in thelearning information storage unit 18, thereby acquiring a firing patterncorresponding to the input information or the one or more pieces offeature information acquired from the input information. In thisexample, the firing pattern is a firing pattern acquired using thelearning information.

There is no limitation on the time at which the firing pattern acquiringunit 36 acquires a firing pattern. The firing pattern acquiring unit 36may regularly acquire a firing pattern, may irregularly acquire a firingpattern, or may acquire a firing pattern each time the judging unit 34detects firing of a soma.

Furthermore, there is no limitation on the temporal interval of thefiring pattern that is acquired by the firing pattern acquiring unit 36.The firing pattern acquiring unit 36 may acquire one or more somaidentifiers that are each paired with timer information indicating thetime that is within a threshold value from the current time or is morerecent than a threshold value, from the firing information storage unit19. The firing pattern acquiring unit 36 may acquire one or more somaidentifiers contained in all pieces of firing information in the firinginformation storage unit 19, from the firing information storage unit19. It is preferable that the temporal interval of the firing patternthat is acquired by the firing pattern acquiring unit 36 dynamicallychanges.

The output information acquiring unit 37 acquires output informationcorresponding to the firing pattern acquired by the firing patternacquiring unit 36, from the output management information storage unit16.

The output information corresponding to the firing pattern is typicallyoutput information that is paired with a firing pattern that is similar,enough to satisfy a predetermined condition, to the firing patternacquired by the firing pattern acquiring unit 36. The case in which afiring pattern A and a firing pattern B are similar enough to satisfy apredetermined condition is, for example, a case in which somaidentifiers in a number that is greater than or equal to a thresholdvalue or is greater than a threshold value, among the one or more somaidentifiers contained in the firing pattern A, are contained in thefiring pattern B. The case in which the firing pattern A and the firingpattern B are similar enough to satisfy a predetermined condition is,for example, a case in which soma identifiers in a number that isgreater than or equal to a threshold value or is greater than athreshold value, among the one or more soma identifiers contained in thefiring pattern B, are contained in the firing pattern A. The case inwhich the firing pattern A and the firing pattern B are similar enoughto satisfy a predetermined condition is, for example, a case in whichsoma identifiers at a proportion that is greater than or equal to athreshold value or is greater than a threshold value, among the one ormore soma identifiers contained in the firing pattern A, are containedin the firing pattern B. The case in which the firing pattern A and thefiring pattern B are similar enough to satisfy a predetermined conditionis, for example, a case in which soma identifiers at a proportion thatis greater than or equal to a threshold value or is greater than athreshold value, among the one or more soma identifiers contained in thefiring pattern B, are contained in the firing pattern A.

For example, the output information acquiring unit 37 detects a firingpattern that is similar, enough to satisfy a predetermined condition, tothe firing pattern acquired by the firing pattern acquiring unit 36,probabilistically judges whether or not the output condition issatisfied, using output probability information that is paired with thefiring pattern, and, if it is judged that the output condition issatisfied, acquires output information that is paired with the outputcondition, from the output management information storage unit 16.

The output information acquiring unit 37 determines an output conditionthat matches the firing pattern acquired by the firing pattern acquiringunit 36 and the one or more pieces of external information accepted bythe input information accepting unit 21, and acquires output informationthat is paired with the output condition. The output informationacquiring unit 37 determines an output condition from among the outputconditions stored in the output management information storage unit 16,and acquires output information that: is paired with the outputcondition.

For example, the output information acquiring unit 37 detects a firingpattern that is similar, enough to satisfy a predetermined condition, tothe firing pattern acquired by the firing pattern acquiring unit 36,from the output management information storage unit 16, and, if it isjudged that one or more pieces of external information that are eachpaired with the firing pattern is similar, enough to satisfy apredetermined condition, to the one or more pieces of externalinformation accepted by the input information accepting unit 21,acquires output information that is paired with the firing pattern andthe one or more pieces of external information in the output managementinformation storage unit 16.

Furthermore, for example, the output information acquiring unit 37detects a firing pattern that is similar, enough to satisfy apredetermined condition, to the firing pattern acquired by the firingpattern acquiring unit 36, from the output management informationstorage unit 16, if it is judged that one or more pieces of externalinformation that are each paired with the firing pattern is similar,enough to satisfy a predetermined condition, to the one or more piecesof external information accepted by the input information accepting unit21, probabilistically judges whether or not the output condition issatisfied, using output probability information that is paired with thefiring pattern and the one or more pieces of external information, and,if it is judged that the output condition is satisfied, acquires outputinformation that is paired with the output condition, from the outputmanagement, information storage unit 16.

The output information acquiring unit 37 cannot always acquire outputinformation.

The control unit 38 performs control such that the processing by thejudging unit 34, the processing by the firing pattern acquiring unit 36,and the processing by the information transfer unit 32 are repeatedtwice or more.

The learning detecting unit 39 detects a learning condition that thefiring pattern acquired by the firing pattern acquiring unit 36 matches.In this example, if some of the soma identifiers of the firing patternacquired by the firing pattern acquiring unit 36 and all or some of thesoma identifiers constituting the firing pattern contained in thelearning condition are similar enough to satisfy a predeterminedcondition, the learning detecting unit 39 judges that the firing patternacquired by the firing pattern acquiring unit 36 matches the learningcondition. The detecting a learning condition is, for example, acquiringa learning condition identifier for identifying a learning condition,acquiring information indicating that the firing pattern matches thelearning condition, or the like.

If the learning detecting unit 39 detects a matching learning condition,the learning information accumulating unit 40 accumulates the learninginformation in the learning information storage unit 18. The learninginformation has input information from which the firing pattern acquiredby the firing pattern acquiring unit 36 is obtained or one or morepieces of feature information acquired from the input information, and afiring pattern having at least some soma identifiers constituting thefiring pattern acquired by the firing pattern acquiring unit 36. Atleast some soma identifiers are, for example, one or more somaidentifiers obtained by excluding the one or more soma identifiers usedto detect the learning condition, from the firing pattern acquired bythe firing pattern acquiring unit 36.

The growth unit 41 performs one or more of soma generation processing,connection information generation processing, connection informationgrowth processing, and glial cell generation processing.

The soma generation processing is processing for generating soma-relatedinformation having a soma identifier. The soma generation processing isprocessing, for example, for generating a unique soma identifier,generating soma positional information of a position that satisfies apredetermined condition, from the position indicated by soma positionalinformation contained in soma-related information of a soma from whichdivision occurred, and accumulating soma-related information having thesoma identifier and the soma positional information in the soma-relatedinformation storage unit 11. It is also possible that part ofinformation constituting generated soma-related information of a soma isNULL (no value).

It is also possible that the soma generation processing is, for example,processing for copying part of information constituting soma-relatedinformation of a soma from which division occurred, and generatingsoma-related information of a divided soma having the information. Theinformation that is copied is, for example, firing conditioninformation. It is preferable that the growth unit 41 sets the somapositional information contained in soma-related information that isgenerated to be information with a position that does not overlap thepositions of other elements. It is preferable that the growth unit 41sets the soma positional information contained in soma-relatedinformation that is generated to be information with a position that isclose, enough to satisfy a predetermined condition, to the positionindicated by the soma positional information of the soma from whichdivision occurred. In the soma generation processing,

The connection information generation processing is processing forgenerating connection information, and accumulating the connectioninformation in the connection information storage unit 13. Theconnection information generation processing is, for example, processingfor acquiring soma identifiers of two somas that are connected to eachother, generating connection information having the two somaidentifiers, and accumulating it in the connection information storageunit 13. The connection information generation processing is, forexample, processing for acquiring an axon identifier of an axon and adendrite identifier of a dendrite that are connected to each other,generating connection information having the two identifiers, andaccumulating it in the connection information storage unit 13. Theconnection information generation processing is, for example, processingfor generating a synapse identifier of a synapse from which informationtransfer is performed and a spine identifier of a spine to whichinformation transfer is performed, generating connection informationhaving the two identifiers, and accumulating it in the connectioninformation storage unit 13.

The connection information growth processing is processing for growingconnection information. The connection information growth processing is,for example, changing the position of axon positional informationcontained in axon information to that in a direction in which the axonextends. The connection information growth processing is, for example,changing the position of dendrite positional information contained indendrite information to that in a direction in which the dendriteextends,

It is preferable that the growth unit 41 performs soma generationprocessing for generating soma-related information of a divided soma,which is a new soma obtained by dividing a soma judged by the judgingunit 34 as a soma that has fired for the number of times or at thefrequency that is large enough to satisfy a predetermined condition, andaccumulating it in the soma-related information storage unit 11.

It is preferable that the growth unit 41 performs connection informationgeneration processing for generating connection information forconnecting a soma judged by the judging unit 34 as a soma that has firedfor the number of times or at the frequency that is large enough tosatisfy a predetermined condition and a divided soma, and accumulatingit in the connection information storage unit 13. The divided soma is asoma obtained by dividing a soma from which generation of the dividedsoma occurred.

It is preferable that the growth unit 41 performs soma generationprocessing for generating soma-related information of a divided soma,which is a new soma obtained by dividing a soma connected to glial cellinformation that satisfies a predetermined condition, and accumulatingit in the soma-related information storage unit 11.

It is preferable that the growth unit 41 performs connection informationgrowth processing for growing an axon or a dendrite connected to glialcell information that satisfies a predetermined condition.

It is preferable that, in the case in which axon positional informationof an axon of one soma and dendrite positional information of a dendriteof another soma are close to each other enough to satisfy apredetermined condition, the growth unit 41 performs connectioninformation generation processing for generating connection informationhaving a soma identifier of the one soma and a soma identifier of theother soma, and accumulating it in the connection information storageunit 13.

It is preferable that the growth unit 41 performs the following glialcell generation processing. That is to say, for example, if the amountof energy held by an element that is a soma, an axon, or a dendritebecomes small, enough to satisfy a predetermined condition, with respectto the necessary energy amount, the growth unit 41 generates glial cellinformation connected to the element. The predetermined condition is,for example, “amount of energy held<necessary energy amount”, “amount ofenergy held≤necessary energy amount”, “amount of energy held−necessaryenergy amount≤threshold value”, or “amount of energy held−necessaryenergy amount <threshold value”. More specifically, for example, thegrowth unit 41 judges whether or not the amount of held energy indicatedby the held energy amount information contained in information of eachelement (soma-related information, axon information, or dendriteinformation) is small, enough to satisfy a predetermined condition, withrespect to the necessary energy amount indicated by the necessary energyamount information contained in the information of the element, and, ifit is judged that the amount of held energy is small, generates glialcell information having an identifier for identifying the element (asoma identifier, an axon identifier, or a dendrite identifier), andaccumulates it in the glial cell information storage unit 14.

The apoptosis processing unit 42 may delete the soma-related informationfrom the soma-related information storage unit 11. It is preferablethat, in the case in which the soma-related information is deleted, theapoptosis processing unit 42 deletes information related to a somacorresponding to the soma-related information, information related to anaxon connected to the soma corresponding to the soma-relatedinformation, and information related to a dendrite connected to the somacorresponding to the soma-related information. That is to say, it ispreferable that the apoptosis processing unit 42 deletes connectioninformation having a soma identifier contained in the deletedsoma-related information, connection information having an axonidentifier contained in the delete soma-related information, andconnection information having a dendrite identifier contained in thedelete soma-related information, from the connection information storageunit 13. In the case of deleting the soma-related information from thesoma-related information storage unit 11, the apoptosis processing unit42 may delete connection information to an axon and a dendrite connectedto a soma corresponding to the soma-related information.

Furthermore, the apoptosis processing unit 42 may delete the axoninformation. The apoptosis processing unit 42 may delete the dendriteinformation. If a soma does not undergo apoptosis, and only an axon or adendrite undergoes apoptosis, for example, the apoptosis processing unit42 deletes axon information of the axon that undergoes apoptosis ordendrite information of the dendrite undergoes apoptosis, from thesoma-related information. In this case, for example, it is preferablethat the apoptosis processing unit 42 deletes connection informationhaving an axon identifier of the axon that undergoes apoptosis orconnection information having a dendrite identifier of the dendriteundergoes apoptosis, from the connection information storage unit 13.

Furthermore, it is preferable that the apoptosis processing unit 42deletes information related to connection with a deleted soma, of aglial cell connected to the soma, from the glial cell informationstorage unit 14. That is to say, for example, the apoptosis processingunit 42 deletes a soma identifier of a deleted soma, from the glial cellinformation containing the soma identifier. If an axon or a dendriteundergoes apoptosis, or a soma connected to an axon or a dendriteundergoes apoptosis, the apoptosis processing unit 42 deletes an axonidentifier of the axon or a dendrite identifier of the dendrite, fromthe glial cell information containing the axon identifier or thedendrite identifier. That is to say, it is preferable that, in the casein which information of a soma, an axon, or a dendrite is deleted, theapoptosis processing unit 42 deletes information of connection with thesoma, the axon, or the dendrite, from the glial cell information.

It is preferable that the apoptosis processing unit 42 deletes thesoma-related information from the soma-related information storage unit11 according to a predetermined condition.

It is preferable that, in the case in which the amount of soma-relatedinformation stored in the soma-related information storage unit 11 islarge enough to satisfy a predetermined condition, the apoptosisprocessing unit 42 deletes the soma-related information from thesoma-related information storage unit 11.

It is preferable that the apoptosis processing unit 42 determines a somathat is not connected to another soma, a dendrite, or an axon, anddeletes soma-related information having a soma identifier of thedetermined soma, from the soma-related information storage unit 11. Forexample, the apoptosis processing unit 42 checks the connectioninformation storage unit 13, acquires a soma identifier that appearedfor the number of times that is less than or equal to a threshold valueor is less than a threshold value, and deletes the soma-relatedinformation containing the soma identifier from the soma-relatedinformation storage unit 11 For example, the apoptosis processing unit42 checks the soma-related information storage unit 11, and deletessoma-related information only having dendrite information that is lessthan or equal to a threshold value or is less than a threshold value oraxon information that is less than or equal to a threshold value or isless than a threshold value, from the soma-related information storageunit 11.

It is preferable that the apoptosis processing unit 42 determines a somaconnected to an axon that does not reach a predetermined goal, anddeletes soma-related information having a soma identifier of thedetermined soma, from the soma-related information storage unit 11. Forexample, the apoptosis processing unit 42 checks the soma-relatedinformation storage unit 11, compares axon positional informationcontained in the soma-related information and goal information,determines a soma connected to an axon that does not reach apredetermined goal, and deletes soma-related information having a somaidentifier of the determined soma, from the soma-related informationstorage unit 11.

It is preferable that the apoptosis processing unit 42 determines a somaidentifier of a soma that has fired for the number of times that issmall enough to satisfy a predetermined condition, using the one or morepieces of firing information in the firing information storage unit 19,and deletes soma-related information having the soma identifier, fromthe soma-related information storage unit 11. For example, the apoptosisprocessing unit 42 determines a soma identifier that appeared for thenumber of times that is less than or equal to a threshold value or isless than a threshold value, and deletes soma-related information havingthe soma identifier, from the soma-related information storage unit 11.

The apoptosis processing unit 42 deletes information related to an axonor information related to a dendrite according to a predeterminedcondition. The information related to an axon is, for example,connection information containing axon information or an axonidentifier, or an axon identifier in glial cell information. Theinformation related to a dendrite is, for example, connectioninformation containing dendrite information or a dendrite identifier, ora dendrite identifier in glial cell information.

For example, if it is judged that the state has reached a saturatedstate and judges that there is an axon or a dendrite connected tonowhere, the apoptosis processing unit 42 deletes information related tothe axon or information related to the dendrite. The reaching asaturated state is a state in which the number of pieces of information,of one or more of the soma-related information, the axon information,the dendrite information, and the glial cell information, is largeenough to satisfy a predetermined condition. That is to say this is astate in which the amount of elements in a space of the informationprocessing apparatus A (apparatus for simulating the brain) is largeenough to satisfy a condition, and the free space therein is less thanor equal to a threshold value or is less than a threshold value. Theelements are somas, axons, dendrites, glial cells, synapses, or spines.

The firing information accumulating unit 43 configures firinginformation having a soma identifier for identifying a soma judged bythe judging unit 34 as a soma that fires, and accumulates the firinginformation in the firing information storage unit 19. For example, thefiring information accumulating unit 43 acquires a soma identifier foridentifying a soma judged by the judging unit 34 as a soma that firesand acquires timer information indicating the current time from anunshown tinier, configures firing information having the soma identifierand the timer information, and accumulates the firing information in thefiring information storage unit 19.

The output unit 5 outputs various types of information. The varioustypes of information are, for example, output information. In thisexample, the output is a concept that encompasses display on a displayscreen, projection using a projector, printing by a printer, output of asound, output of a vibration using a vibrator, transmission to anexternal apparatus, accumulation in a storage medium, delivery of aprocessing result to another processing apparatus or another program,and the like.

The information output unit 51 outputs the output information acquiredby the output information acquiring unit 37. There is no limitation onthe output destination of the output information. The output informationmay be output to the outside of the information processing apparatus A,or may be delivered to another process in the information processingapparatus A, for example.

The storage unit 1, the soma-related information storage unit 11, thesoma group information storage unit 12, the connection informationstorage unit 13, the glial cell information storage unit 14, the firingstart point information storage unit 15, the output managementinformation storage unit 16, the learning condition storage unit 17, thelearning information storage unit 18, the firing information storageunit 19, and the used connection information storage unit 20 arepreferably non-volatile storage media, but may be realized also byvolatile storage media.

There is no limitation on the procedure in which information is storedin the storage unit 1 and the like. For example, information may bestored in the storage unit 1 and the like via a storage medium,information transmitted via a communication line or the like may bestored in the storage unit 1 and the like, or information input via aninput device may be stored in the storage unit 1 and the like.

The processing unit 3, the feature information acquiring unit 31, theinformation transfer unit 32, the soma calculating unit 33, the judgingunit 34, the firing probability changing unit 35, the firing patternacquiring unit 36, the output information acquiring unit 37, the controlunit 38, the learning detecting unit 39, the learning informationaccumulating unit 40, the growth unit 41, the apoptosis processing unit42, and the firing information accumulating unit 43 may be realizedtypically by MPUs, memories, or the like. Typically, the processingprocedure of the processing unit 3 and the like is realized by software,and the software is stored in a storage medium such as a ROM. Note thatthe processing procedure may be realized also by hardware (dedicatedcircuits).

The output unit 5 and the information output unit 51 may be consideredto include or not to include an output device, such as a display screenor a speaker. The output unit 5 and the like may be realized, forexample, by driver software for an output device, a combination ofdriver software for an output device and the output device, or the like.

Next, an operation example of the information processing apparatus Awill be described with reference to the flowchart in FIG. 3.

(Step S301) The input information accepting unit 21 accepts externalinformation, and temporarily stores it in the storage unit 1. In thisexample, the input information accepting unit 21 may not accept externalinformation.

(Step S302) The input information accepting unit 21 judges whether ornot it has accepted input information. If it has accepted inputinformation, the procedure advances to step S303, and, if not, theprocedure advances to step S304.

(Step S303) The information processing apparatus A performs firingtransfer processing. The procedure returns to step S301. The firingtransfer processing is processing for transferring information betweensomas. Later, an example of the firing transfer processing will bedescribed in detail with reference to the flowchart in FIG. 4.

(Step S304) The processing unit 3 judges whether or not to performfiring pattern processing. If firing pattern processing is to beperformed, the procedure advances to step S305, and, if not, theprocedure advances to step S306. The processing unit 3 may always judgeto perform firing pattern processing, or may judge to perform firingpattern processing at predetermined intervals. There is no limitation onthe conditions for judging whether or not to perform firing patternprocessing.

(Step S305) The information processing apparatus A performs firingpattern processing. The procedure returns to step S301. The firingpattern processing is processing performed using a firing pattern, and,for example, includes processing for determining output informationusing a firing pattern and outputting the output, information, andlearning processing. Later, an example of the firing pattern processingwill be described in detail with reference to the flowchart in FIG. 6.

(Step S306) The processing unit 3 judges whether or not to performgrowth processing and apoptosis processing. If growth processing and thelike are to be performed, the procedure advances to step S307, and, ifriot, the procedure returns to step S301. The processing unit 3 mayalways judge to perform growth processing and the like, or may judge toperform growth processing and the like at predetermined intervals. Thereis no limitation on the conditions for judging whether or not to performgrowth processing and the like. It is also possible to perform thegrowth processing and the apoptosis processing as a set, or toindividually judge whether or not to perform them.

(Step S307) The growth unit 41 performs soma growth processing. The somagrowth processing will be described with reference to the flowchart inFIG. 7.

(Step S308) The growth unit 41 performs axon growth processing. The axongrowth processing will be described with reference to the flowchart inFIG. 8.

(Step S309) The growth unit 41 performs dendrite growth processing. Thedendrite growth processing will be described with reference to theflowchart in FIG. 9.

(Step S310) The growth unit 41 performs soma connection processing. Thesoma connection processing will be described with reference to theflowchart in FIG. 10.

(Step S311) The growth unit 41 performs glial cell growth processing.The glial cell growth processing will be described with reference to theflowchart in FIG. 11.

(Step S312) The apoptosis processing unit 42 performs apoptosisprocessing. The procedure returns to step S301. The apoptosis processingwill be described with reference to the flowchart in FIG. 12.

In the flowchart in FIG. 3, it is preferable to perform the firingtransfer processing, the firing pattern processing, the growthprocessing, the apoptosis processing, and the like in parallel. Also, itis preferable to perform the firing transfer processing in somas inparallel.

Note that the procedure is terminated by powering off or an interruptionat the end of the process in the flowchart in FIG. 3.

Hereinafter, an example of the firing transfer processing in step S303will be described in detail with reference to the flowchart in FIG. 4.

(Step S401) The feature information acquiring unit 31 acquires one ormore pieces of feature information. The feature information acquiringunit 31 acquires one or more pieces of feature information, for example,using any one of the methods (1) to (3) below. (1) The featureinformation acquiring unit 31 analyzes the input information accepted instep S201, thereby acquiring one or more pieces of feature information.In this example, the one or more pieces of feature information are, forexample, one or more pairs of an information identifier and aninformation amount. (2) The information transfer unit 32 acquires one ormore pieces of feature information applied to soma-related informationof a soma judged as a soma that fires. In this example, the one or morepieces of feature information are, for example, one information amount.(3) The information transfer unit 32 acquires one or more pieces offeature information, from one or more pieces of feature informationapplied to soma-related information of a soma judged as a soma thatfires. In (3), the information transfer unit 32 calculates each of theone or more pieces of feature information accepted by a soma judged as asoma that fires, using a predetermined calculation formula, therebyacquiring one or more pieces of feature information. Examples of thecalculation include addition.

(Step S402) The information transfer unit 32 determines one or moresomas to which the one or more pieces of feature information acquired instep S401 are to be delivered. Such somas are determined, for example,using any one of the methods (1) to (3) below. (1) The informationtransfer unit 32 acquires soma identifiers of predetermined one or moresomas, from the soma-related information in the soma-related informationstorage unit 11. The soma identifiers of predetermined one or more somasare stored, for example, in the storage unit 1, and the informationtransfer unit 32 acquires such one or more soma identifiers from thestorage unit 1. The one or more soma identifiers are soma identifiers ofsomas that first accept one or more pieces of feature informationacquired from the input information accepted from the outside. (2) Theinformation transfer unit 32 acquires, from the firing start pointinformation storage unit 15, one or more soma identifiers that arerespectively paired with information identifiers contained in thefeature information acquired by the feature information acquiring unit31. (3) The information transfer unit 32 acquires soma identifiers ofone or more somas connected to an end of a soma that is to be processed,referring to the connection information storage unit 13. That is to say,for example, the information transfer unit 32 realizes the processing(3) through any one of the processes (a) to (c) below. (a) Theinformation transfer unit 32 acquires, for example, dendrite identifiersthat are respectively paired with one or more axon identifiers containedin soma-related information of a soma that is to be processed, from theconnection information storage unit 13. The information transfer unit 32acquires, for example, one or more soma identifiers contained insoma-related information having the acquired one or more dendriteidentifiers, from the soma-related information storage unit 11. (b) Theinformation transfer unit 32 acquires, for example, one or more somaidentifiers that are respectively paired with soma identifiers containedin soma-related information of a soma that is to be processed, from theconnection information storage unit 13. (c) The information transferunit 32 acquires, for example, spine identifiers that are respectivelypaired with one or more synapse identifiers contained in soma-relatedinformation of a soma that is to be processed, from the connectioninformation storage unit 13. The information transfer unit 32 acquires,for example, one or more soma identifiers contained in soma-relatedinformation having the acquired one or more spine identifiers, from thesoma-related information storage unit 11.

(Step S403) The processing unit 3 substitutes 1 for a counter i.

(Step S404) The processing unit 3 judges whether or not there is ani^(-th) soma in the one or more somas determined in step S402. If thereis an i^(-th) soma, the procedure advances to step S405, and, if not,the procedure returns to the upper-level processing. Typically theprocessing unit 3 judges whether or not there is an i^(-th) soma, basedon whether or not there is an i^(-th) soma identifier in the somaidentifiers acquired in step S402.

(Step S405) The judging unit 34 performs firing judgment processing. Thefiring judgment processing will be described in detail with reference tothe flowchart in FIG. 5.

(Step S406) If the judgment result in step S405 is “a soma fires”, theprocessing unit 3 causes the procedure to advance to step S407, and, ifnot, the procedure advances to step S411.

(Step S407) The firing information accumulating unit 43 configuresfiring information having a soma identifier for identifying a somajudged by the judging unit 34 as a soma that fires. The firinginformation accumulating unit 43 accumulates the firing information inthe firing information storage unit 19. In this example, it ispreferable that the firing information accumulating unit 43 acquirestinier information from an unshown timer, configures firing informationhaving the soma identifier and the tuner information, and accumulates itin the firing information storage unit 19.

(Step S408) The firing probability changing unit 35 changes the firingprobability information that is paired with a soma identifier of thesoma judged by the judging unit 34 as a soma that fires, so as toincrease the firing probability The firing probability information thatis changed is information that is stored in the soma-related informationstorage unit 11.

(Step S409) The processing unit 3 judges whether or not to end featureinformation transfer to a soma that is at an end of the i^(-th) soma ora soma group that is at an end of the i^(-th) soma. If the transfer isto be ended, the procedure advances to step S411, and, if not, theprocedure advances to step S410. The processing unit 3 judges whether ornot there is a soma that is at an end of the i^(-th) soma, for example,referring to the connection information storage unit 13. If there is nosoma that is at an end of the i^(-th) soma, the feature informationtransfer is ended. If there is no dendrite that is at an end of an axonconnected to the i^(-th) soma, information transfer is performed fromthe soma to the axon, but, there is no part that receives theinformation from the axon, and thus the information transfer is stopped.Also in this case, the processing unit 3 judges to end the featureinformation transfer.

(Step S410) The processing unit 3 performs firing transfer processing tothe soma that is at an end of the i^(-th) soma or the soma group that isat an end of the i^(-th) soma. This processing is firing transferprocessing. That is to say, the firing transfer processing is recursiveprocessing.

(Step S411) The processing unit 3 increments the counter i by 1. Theprocedure returns to step S404.

Next, the firing judgment processing in step S405 will be described indetail with reference to the flowchart in FIG. 5.

(Step S501) The judging unit 34 acquires firing condition informationcontained in soma-related information of the soma that is to beprocessed, from the soma-related information storage unit 11,

(Step S502) The judging unit 34 judges whether or not externalinformation has been accepted in step S301. If external information hasbeen accepted, the procedure advances to step S503, and, if not, theprocedure advances to step S504.

(Step S503) The judging unit 34 acquires the external informationaccepted in step S302, or one or more pieces of feature informationacquired from the external information. The processing for acquiring oneor more pieces of feature information from external information may beperformed by the feature information acquiring unit 31, or may beperformed by the judging unit 34 or the like.

(Step S504) The judging unit 34 applies the one or more pieces offeature information and the like to the firing condition informationacquired in step S501, and judges whether or not the soma fires. The oneor more pieces of feature information and the like are one or morepieces of feature information, or one or more pieces of featureinformation and external information.

(Step S505) The judging unit 34 substitutes the judgment result in stepS504 to a variable “return value”. The procedure returns to theupper-level processing.

Next, an example of the firing pattern processing in step S305 will bedescribed in detail with reference to the flowchart in FIG. 6.

(Step S601) The firing pattern acquiring unit 36 acquires a firingpattern having one or more soma identifiers, referring to the firinginformation storage unit 19. It is preferable that the firing patternacquiring unit 36 also acquires a firing pattern corresponding to inputinformation or one or more pieces of feature information acquired fromthe input information, from the learning information storage unit 18.That is to say it is preferable to use a firing pattern obtained throughlearning in association with input information as well to the followingprocessing.

(Step S602) The output information acquiring unit 37 judges whether ornot external information has been accepted in step S301. If externalinformation has been accepted, the procedure advances to step S603, and,if not, the procedure advances to step S604.

(Step S603) The output information acquiring unit 37 acquires theexternal information accepted in step S301, or one or more pieces offeature information acquired from the external information. Theprocessing for acquiring one or more pieces of feature information fromexternal information may be performed by the feature informationacquiring unit 31, or may be performed by the output informationacquiring unit 37 or the like. The external information accepted in stepS301 is typically external information that is stored in the storageunit 1.

(Step S604) The output information acquiring unit 37 substitutes 1 for acounter

(Step S605) The output information acquiring unit 37 judges whether ornot there is an i^(-th) piece of output management information in theoutput management information storage unit 16. If there is an i^(-th)piece of output management information, the procedure advances to stepS606, and, if not, the procedure advances to step S611.

(Step S606) The output information acquiring unit 37 acquires an outputcondition contained in the i^(-th) piece of output managementinformation, from the output management information storage unit 16.

(Step S607) The output information acquiring unit 37 judges whether ornot the firing pattern acquired in step S601, or the firing patternacquired in step S601 and the information acquired in step S603 matchthe output condition acquired in step S606. If they match the outputcondition, the procedure advances to step S608, and, if not, theprocedure advances to step S610.

(Step S608) The output information acquiring unit 37 acquires outputinformation contained in the i ^(-th) piece of output managementinformation.

(Step S609) The information output unit 51 outputs the outputinformation acquired in step S608.

(Step S610) The output information acquiring unit 37 increments thecounter i by 1. The procedure returns to step S605.

(Step S611) The learning information accumulating unit 40 acquires inputinformation or the one or more pieces of feature information acquiredfrom the input information.

(Step S612) The learning detecting unit 39 substitutes 1 for a counteri.

(Step S613) The learning detecting unit 39 judges whether or not thereis an i^(th) learning condition in the learning condition storage unit17. If there is an i^(th) learning condition, the procedure advances tostep S614, and, if not, the procedure advances to step S617.

(Step S614) The learning detecting unit 39 judges whether or not thefiring pattern acquired in step S601 matches the i^(-th) learningcondition. If they match each other, the procedure advances to stepS615, and, if not, the procedure advances to step S617.

(Step S615) The learning information accumulating unit 40 acquires oneor more soma identifiers that are to be accumulated, from the firingpattern acquired in step S601. The learning information accumulatingunit 40 configures learning information having the one or more somaidentifiers, and the input information or one or more pieces of featureinformation acquired in step S611. The one or more soma identifiers area firing pattern.

(Step S616) The learning information accumulating unit 40 accumulatesthe learning information configured in step S615.

(Step S617) The learning detecting unit 39 increments the counter iby 1. The procedure returns to step S613.

In the flowchart in FIG. 6, the processing in steps S601 to S610 isoutput processing of output information, and the processing in stepsS611 to step S617 is learning processing.

Next, an example of the soma growth processing in step S307 will bedescribed with reference to the flowchart in FIG. 7.

(Step S701) The growth unit 41 substitutes 1 for a counter i.

(Step S702) The growth unit 41 judges whether or not there is an i^(-th)piece of soma-related information in the soma-related informationstorage unit 11. If there is an i^(-th) piece of soma-relatedinformation, the procedure advances to step S703, and, if not, theprocedure returns to the upper-level processing.

(Step S703) The growth unit 41 acquires firing information correspondingto an i^(-th) soma identifier contained in the i^(-th) piece ofsoma-related information, from the firing information storage unit 19.The firing information is a history of firing of the i^(-th) soma. Thegrowth unit 41 judges whether or not the acquired firing informationsatisfies a condition. If the firing information satisfies a condition,the procedure advances to step S704, and, if not, the procedure advancesto step S708. The growth unit 41 judges from the acquired firinginformation that it satisfies a condition, for example, if a soma isfiring well enough to satisfy a predetermined condition. That is to saythe growth unit 41 judges whether or not, the number of pieces of firinginformation containing the soma identifier is large enough to satisfy apredetermined condition. If the number is large, it is judged that thecondition is satisfied. The firing information that is acquired by thegrowth unit 41 may be, for example, firing information having timerinformation within a predetermined period from the current time.

(Step S704) The growth unit 41 acquires information related to glialcell information corresponding to the i^(-th) soma. In this example, theinformation related to glial cell information may be glial cellinformation of one or more glial cells connected to the i^(-th) soma, ormay be the number of glial cells connected to the i^(-th) soma, or thelike.

(Step S705) The growth unit 41 judges whether or not the informationrelated to glial cell information acquired in step S704 satisfies apredetermined condition. If the information satisfies a condition, theprocedure advances to step S706, and, if not, the procedure advances tostep S708. The predetermined condition is a condition for generating achild soma. The predetermined condition is a case in which theinformation related to glial cell information is information indicatingthat the number of glial cells is large enough to satisfy apredetermined condition. For example, the growth unit 41 calculates thenumber of glial cell identifiers that are each paired with the i^(-th)soma identifier, and, if the number is greater than or equal to athreshold value or is greater than a threshold value, judges that theinformation satisfies the predetermined condition. In this example, itis also possible that the growth unit 41 judges that the informationsatisfies the condition if the number of elements, among the number ofpieces of soma-related information, the number of pieces of axoninformation, the number of pieces of dendrite information, and the like,is less than a threshold value or is less than or equal to a thresholdvalue.

(Step S706) The growth unit 41 generates soma-related information of adivided soma obtained by dividing the i^(-th) soma, and accumulates itin the soma-related information storage unit 11. There is no limitationon the algorithm for the growth unit 41 to generate soma-relatedinformation of a child soma.

(Step S707) The growth unit 41 generates connection information forconnecting the i^(-th) soma and the divided soma generated in step S706,and accumulates it in the connection information storage unit 13.

(Step S708) The growth unit 41 increments the counter i by 1. Theprocedure returns to step S702.

Next, an example of the axon growth processing in step S308 will bedescribed with reference to the flowchart in FIG. 8.

(Step S801) The growth unit 41 substitutes 1 for a counter i.

(Step S802) The growth unit 41 judges whether or not there is an i^(-th)piece of axon information in the soma-related information storage unit11. If there is an piece of axon information, the procedure advances tostep S803, and, if not, the procedure returns to the upper-levelprocessing.

(Step S803) The growth unit 41 acquires information related to glialcell information corresponding to the i^(-th) to piece of axoninformation. In this example, the information related to glial cellinformation may be glial cell information of one or more glial cellsconnected to an i^(-th) axon, or may be the number of glial cellsconnected to the i^(-th) axon, or the like.

(Step S804) The growth unit 41 judges whether or not the informationrelated to glial cell information acquired in step S803 satisfies apredetermined condition. If the information satisfies a condition, theprocedure advances to step S805, and, if not, the procedure advances tostep S806. The predetermined condition is a condition for allowing anaxon to extend. The predetermined condition is a case in which theinformation related to glial cell information is information indicatingthat the number of glial cells is large enough to satisfy apredetermined condition.

(Step S805) The growth unit 41 changes the axon positional informationcontained in the i^(-th) piece of axon information, so as to allow theaxon to extend.

(Step S806) The growth unit 41 increments the counter i by 1. Theprocedure returns to step S802.

Next, the dendrite growth processing in step S309 will be described withreference to the flowchart in FIG. 9.

(Step S901) The growth unit 41 substitutes 1 for a counter i.

(Step S902) The growth unit 41 judges whether or not there is an i^(-th)piece of dendrite information in the soma-related information storageunit 11. If there is an i^(-th) piece of dendrite information, theprocedure advances to step S903, and, if riot, the procedure returns tothe upper-level processing.

(Step S903) The growth unit 41 acquires information related to glialcell information corresponding to the i^(-th) piece of dendriteinformation. In this example, the information related to glial cellinformation may be glial cell information of one or more glial cellsconnected to an i^(-th) dendrite, or may be the number of glial cellsconnected to the i^(-th) dendrite, or the like.

(Step S904) The growth unit 41 judges whether or not the informationrelated to glial cell information acquired in step S903 satisfies apredetermined condition. If the information satisfies a condition, theprocedure advances to step S905, and, if not, the procedure advances tostep S906. The predetermined condition is a condition for allowing adendrite to extend. The predetermined condition is a case in which theinformation related to glial cell information is information indicatingthat the number of glial cells is large enough to satisfy apredetermined condition.

(Step S905) The growth unit 41 changes the dendrite positionalinformation contained in the i^(-th) piece of dendrite information, soas to allow the dendrite to extend.

(Step S906) The growth unit 41 increments the counter i by 1. Theprocedure returns to step S902.

Next, the soma connection processing in step S310 will be described withreference to the flowchart in FIG. 10.

(Step S1001) The growth unit 41 substitutes 1 for a counter i.

(Step S1002) The growth unit 41 judges whether or not there is ani^(-th) piece of axon information in the soma-related informationstorage unit 11. If there is an i^(-th) piece of axon information, theprocedure advances to step S1003, and, if not, the procedure returns tothe upper-level processing.

(Step S1003) The growth unit 41 acquires axon positional informationcontained in the i^(-th) piece of axon information, from thesoma-related information storage unit 11.

(Step S1004) The growth unit 41 substitutes 1 for a counter j.

(Step S1005) The growth unit 41 judges whether or not there is a j^(-th)piece of dendrite information that is not input to a soma connected tothe i^(-th) axon and that is dendrite information of a dendrite, in thesoma-related information storage unit 11. If there is a j^(-th) piece ofdendrite information, the procedure advances to step S1006, and, if not,the procedure advances to step S1010.

(Step S1006) The growth unit 41 acquires dendrite positional informationcontained in the j^(-th) piece of dendrite information, from thesoma-related information storage unit 11.

(Step S1007) The growth unit 41 judges whether or not the i^(-th) axonand the j^(-th) dendrite can be connected to each other, using the axonpositional information contained in the i^(-th) piece of axoninformation and the dendrite positional information contained in thej^(-th) piece of dendrite information. If they can be connected to eachother, the procedure advances to step S1008, and, if not, the procedureadvances to step S1009. For example, the growth unit 41 judges that thei^(-th) axon and the j^(-th) dendrite can be connected to each other, ifit is determined that there is an overlapping point between the axonpositional information contained in the i^(-th) piece of axoninformation and the dendrite positional information contained in thej^(-th) piece of dendrite information. For example, the growth unit 41judges that the i^(-th) axon and the j^(-th) dendrite can be connectedto each other, if it is determined that the position at an end of anaxon indicated by the axon positional information contained in thei^(-th) piece of axon information and the position at an end of adendrite indicated by the dendrite positional information contained inthe j^(-th) piece of dendrite information match each other or are withina distance that is less than or equal to a threshold value or is lessthan a threshold value.

(Step S1008) The growth unit 41 configures connection information forspecifying connection between the i^(-th) axon and the j^(-th) dendrite,and accumulates it in the connection information storage unit 13. Forexample, the growth unit 41 configures connection information having anaxon identifier contained in the i^(-th) piece of axon information and adendrite identifier contained in the j^(-th) piece of dendriteinformation, and accumulates it in the connection information storageunit 13.

(Step S1009) The growth unit 41 increments the counter j by 1. Theprocedure returns to step S1005.

(Step S1010) The growth unit 41 increments the counter i by 1. Theprocedure returns to step S1002.

Next, the glial cell growth processing in step S311 will be describedwith reference to the flowchart in FIG. 11.

(Step S1101) The growth unit 41 substitutes 1 for a counter i.

(Step S1102) The growth unit 41 judges whether or not there is ani^(-th) piece of soma-related information in the soma-relatedinformation storage unit 11. If there is an i^(-th) piece ofsoma-related information, the procedure advances to step S1103, and, ifnot, the procedure returns to the upper-level processing.

(Step S1103) The growth unit 41 acquires the necessary energy amountinformation and the held energy amount information contained in thei^(-th) piece of soma-related information.

(Step S1104) The growth unit 41 judges whether or not the necessaryenergy amount information and the held energy amount informationacquired in step S1103 satisfy a predetermined condition. If theysatisfy a predetermined condition, the procedure advances to step S1105,and, if not, the procedure advances to step S1107.

(Step S1105) The growth unit 41 acquires a soma identifier contained inthe i^(-th) piece of soma-related information.

(Step S1106) The growth unit 41 configures glial cell information havingthe soma identifier acquired in step S1105, and accumulates it in theglial cell information storage unit 14.

(Step S1107) The growth unit 41 substitutes 1 for a counter j.

(Step S1108) The growth unit 41 judges whether or not there is a j^(-th)piece of axon information in the i ^(-th) piece of soma-relatedinformation. If there is a j^(-th) piece of axon information, theprocedure advances to step S1109, and, if not, the procedure advances tostep S1114.

(Step S1109) The growth unit 41 acquires the necessary energy amountinformation and the held energy amount information contained in thej^(-th) piece of axon information.

(Step S1110) The growth unit 41 judges whether or not the necessaryenergy amount information and the held energy amount informationacquired in step S1109 satisfy a predetermined condition. If theysatisfy a predetermined condition, the procedure advances to step S1111,and, if not, the procedure advances to step S1113.

(Step S1111) The growth unit 41 acquires an axon identifier of thej^(-th) piece of axon information.

(Step S1112) The growth unit 41 configures glial cell information havingthe axon identifier acquired in step S1111, and accumulates it in theglial cell information storage unit 14.

(Step S1113) The growth unit 41 increments the counter j by 1. Theprocedure returns to step S1108.

(Step S1114) The growth unit 41 substitutes 1 for a counter j.

(Step S1115) The growth unit 41 judges whether or not there is a j^(-th)piece of dendrite information in the i^(-th) piece of soma-relatedinformation. If there is j^(-th) piece of dendrite information, theprocedure advances to step S1116, and, if not, the procedure advances tostep S1121.

(Step S1116) The growth unit 41 acquires the necessary energy amountinformation and the held energy amount information contained in thej^(-th) piece of dendrite information.

(Step S1117) The growth unit 41 judges whether or not the necessaryenergy amount information and the held energy amount informationacquired in step S1116 satisfy a predetermined condition. If theysatisfy a predetermined condition, the procedure advances to step S1118,and, if not, the procedure advances to step S1120.

(Step S1118) The growth unit 41 acquires a dendrite identifier of thej^(-th) piece of dendrite information.

(Step S1119) The growth unit 41 configures glial cell information havingthe dendrite identifier acquired in step S1118, and accumulates it inthe glial cell information storage unit 14.

(Step S1120) The growth unit 41 increments the counter j by 1. Theprocedure returns to step S1115.

(Step S1121) The growth unit 41 increments the counter i by 1. Theprocedure returns to step S1102.

Next, the apoptosis processing in step S312 will be described withreference to the flowchart in FIG. 12.

(Step S1201) The apoptosis processing unit 42 substitutes 1 for acounter i.

(Step S1202) The apoptosis processing unit 42 judges whether or notthere is an i^(-th) piece of soma-related information in thesoma-related information storage unit 11. If there is an i^(-th) pieceof soma-related information, the procedure advances to step S1203, and,if not, the procedure returns to the upper-level processing.

(Step S1203) The apoptosis processing unit 42 acquires a soma identifierof the i^(-th) piece of soma-related information from the soma-relatedinformation storage unit 11.

(Step S1204) The apoptosis processing unit 42 acquires firinginformation containing the soma identifier acquired in step S1203, fromthe firing information storage unit 19. In this example, it ispreferable that the firing information that is acquired is firinginformation having timer information indicating the time that is withina threshold value from the current time or is more recent than athreshold value.

(Step S1205) The apoptosis processing unit 42 judges whether or not anapoptosis condition is satisfied, using the firing information acquiredin step S1204. If an apoptosis condition is satisfied, the procedureadvances to step S1206, and, if not, the procedure advances to stepS1208.

(Step S1206) The apoptosis processing unit 42 deletes the i^(-th) pieceof soma-related information from the soma-related information storageunit 11.

(Step S1207) The apoptosis processing unit 42 deletes connectioninformation corresponding to the i^(-th) soma from the connectioninformation storage unit 13.

(Step S1208) The apoptosis processing unit 42 increments the counter iby 1. The procedure returns to step S1202.

As described above, according to this embodiment, it is possible torealize an information processing apparatus for simulating processing inthe brain.

Furthermore, according to this embodiment, it is possible to realize aninformation processing apparatus for simulating information deliveryprocessing between soma groups.

Furthermore, according to this embodiment, it is possible to realize aninformation processing apparatus for simulating dendrites and axons inthe brain.

Furthermore, according to this embodiment, it is possible to realize aninformation processing apparatus for simulating synapses and spines inthe brain.

Furthermore, according to this embodiment, it is possible to realize aninformation processing apparatus for simulating processing in the brainin which a soma that has operated once does not operate as long as thelength of time that has elapsed is not long enough to satisfy apredetermined condition.

Furthermore, according to this embodiment, it is possible to realize aninformation processing apparatus for simulating processing in the brainin which a soma that has fired is likely to fire.

Furthermore, according to this embodiment, it is possible to realize aninformation processing apparatus for simulating processing in the brainin which, even when the same input information is given, outputinformation varies depending on external information.

Furthermore, according to this embodiment, it is possible to realize aninformation processing apparatus for simulating processing in the brainin which learning of firing patterns is performed.

Furthermore, according to this embodiment, it is possible to realize aninformation processing apparatus for simulating processing in the brainin which somas and the like grow.

Furthermore, according to this embodiment, it is possible to realize aninformation processing apparatus for simulating a growth method of somasand the like in the brain.

Furthermore, according to this embodiment, it is possible to realize aninformation processing apparatus for simulating glial cells in thebrain.

Furthermore, according to this embodiment, it is possible to realize aninformation processing apparatus for simulating processing in the brainin which the number of somas in the brain automatically decreases.

Furthermore, according to this embodiment, it is possible to realize aninformation processing apparatus for simulating apoptosis of somas inthe brain.

Moreover, according to this embodiment, it is possible to realize aninformation processing apparatus for more specifically simulating growthof somas and the like in the brain.

The processing in this embodiment may be realized by software. Thesoftware may be distributed by software downloads or the like.Furthermore, the software may be distributed in a form where thesoftware is stored in a storage medium such as a CD-ROM. Note that thesame is applied to other embodiments described in this specification.The software that realizes the information processing apparatus A inthis embodiment is the following sort of program. Specifically, thisprogram is a program using a computer-accessible storage mediumincluding: a soma-related information storage unit in which two or morepieces of soma-related information having a soma identifier foridentifying a soma, and firing condition information related to acondition for the soma to fire are stored; a connection informationstorage unit in which one or more pieces of connection information forspecifying connection between two or more somas are stored; and anoutput management information storage unit in which one or more piecesof output management information having an output condition, which is acondition for output using a firing pattern having one or more somaidentifiers, and output information, which is information that isoutput, are stored, the program causing a computer to function as: aninput information accepting unit that accepts input information; afeature information acquiring unit that acquires one or more pieces offeature information from the input information; an information transferunit that acquires the one or more pieces of feature informationacquired by the feature information acquiring unit and one or more somaidentifiers each for identifying a soma that fires first, and acquiresone or more pieces of feature information given from one or more othersomas or one or more pieces of feature information acquired from the oneor more pieces of feature information, and a soma identifier of each ofone or more somas that are to be subjected to judgment of firing; ajudging unit that, using the one or more pieces of feature informationacquired by the information transfer unit, and firing conditioninformation that is paired with the one or more soma identifiersacquired by the information transfer unit, judges whether or not thesoma identified with each of the soma identifiers fires; a firingpattern acquiring unit that acquires a firing pattern containing one ormore soma identifiers each for identifying a soma judged by the judgingunit as a soma that fires; an output information acquiring unit thatacquires, from the output management information storage unit, outputinformation corresponding to the firing pattern acquired by the firingpattern acquiring unit; and an information output unit that outputs theoutput information acquired by the output information acquiring unit,wherein the information transfer unit acquires the soma identifier ofeach of the one or more somas connected to the soma judged by thejudging unit as a soma that fires, using the one or more pieces offeature information applied to soma-related information of the somajudged by the judging unit as a soma that fires or one or more pieces offeature information acquired from the one or more pieces of featureinformation, and the connection information in the connectioninformation storage unit, and the processing by the judging unit, theprocessing by the firing pattern acquiring unit, and the processing bythe information transfer unit are repeated twice or more.

Embodiment 2

In this embodiment, an information processing apparatus will bedescribed that determines and outputs output information correspondingto input information using one or more somas, wherein the number ofsomas automatically increases.

Furthermore, in this embodiment, an information processing apparatuswill be described in which elements have positional information, andgrowth and connection of the elements are realized using the positionalinformation.

Furthermore, in this embodiment, an information processing apparatuswill be described that has glial cell information, wherein the glialcell information affects growth.

Furthermore, in this embodiment, an information processing apparatuswill be described that simulates how an axon and the like actually grow.

Moreover, in this embodiment, an information processing apparatus willbe described that simulates apoptosis processing of cells such as somas.

FIG. 13 is a block diagram of a first example of an informationprocessing apparatus B in this embodiment. FIG. 14 is a block diagram ofa second example of the information processing apparatus B in thisembodiment. FIG. 14 is a view obtained by deleting some constituentelements from FIG. 13.

In FIG. 14, the information processing apparatus B includes, forexample, an apparatus that inputs input information to a neural network,and receives output of output information from the neural network thathas accepted the input information. The information processing apparatusB performs processing for automatically generating nodes constituting aneural network or automatically deleting nodes constituting a neuralnetwork.

In FIG. 13, the information processing apparatus B includes a storageunit 6, the accepting unit 2, a processing unit 7, and the output unit5.

The storage unit 6 includes a soma-related information storage unit 61,a connection information storage unit 12, a glial cell informationstorage unit 13, an output management information storage unit 14, alearning condition storage unit 15, a learning information storage unit16, and a firing information storage unit 17. The accepting unit 2includes the input information accepting unit 21. The processing unit 7includes the feature information acquiring unit 31, the connectiondetecting unit 32, an information transfer unit 71, the judging unit 34,the firing probability changing unit 35, the firing pattern acquiringunit 36, the output information acquiring unit 37, the control unit 38,the learning detecting unit 39, the learning information accumulatingunit 40, a growth unit 72, the apoptosis processing unit 42, and thefiring information accumulating unit 43. The output unit 5 includes theinformation output unit 51.

In FIG. 14, the information processing apparatus B includes a storageunit 8, the accepting unit 2, a processing unit 9, and the output unit5.

The storage unit 8 includes the soma-related information storage unit 61and the connection information storage unit 12. The processing unit 9includes the information transfer unit 71, an output informationacquiring unit 73, the growth unit 72, and the apoptosis processing unit42. The output unit 5 includes the information output unit 51.

In the storage unit 6, various types of information are stored. Thevarious types of information are, for example, soma-related information,connection information, and the like.

In the soma-related information storage unit 61, two or more pieces ofsoma-related information are stored. The soma-related information isinformation related to a soma. In this example, the soma may beconsidered as a node constituting a neural network.

The soma-related information has a soma identifier for identifying asoma. The soma-related information may also have firing conditioninformation related to a condition for the soma to fire. The firingcondition information may be present for each soma, may be common to twoor more somas, may be present for each soma group, or may be common toall somas.

The soma-related information may have soma positional informationindicating a position of a soma. The soma-related information may haveone or more pieces of dendrite information and one or more pieces ofaxon information. The soma-related information may have a soma groupidentifier for identifying a soma group, which is a group to which asoma belongs.

Note that the soma-related information storage unit 61 may be the sameas the soma-related information storage unit 11.

The processing unit 7 or the processing unit 9 performs various types ofprocessing. The various types of processing are, for example, processesthat are performed by the information transfer unit 71, the growth unit72, and the like.

The information transfer unit 71 acquires soma identifiers of one ormore somas that accept information based on the input information. Theinformation based on the input information is one or at least twofeature amounts acquired from the input information, part of the inputinformation, information acquired from another soma, or the like.

The information transfer unit 71 may perform information transferbetween nodes in a known neural network. The information transferprocessing includes processing for acquiring a soma identifier that isan identifier of a next node (soma, in this example) to whichinformation is to be transferred.

For example, the information transfer unit 71 acquires one or more somaidentifiers each for identifying a soma that acquires information first,using input information or information acquired from the inputinformation, and acquires one or more soma identifiers each foridentifying a soma that acquires information from one or more othersomas.

It is also possible that the information transfer unit 71 acquires theone or more pieces of feature information acquired by the featureinformation acquiring unit 31 and one or more soma identifiers each foridentifying a soma that fires first, and acquires one or more pieces offeature information given from one or more other somas or one or morepieces of feature information acquired from the one or more pieces offeature information, and a soma identifier of each of one or more somasthat are to be subjected to judgment of firing.

It is also possible that the information transfer unit 71 acquires asoma identifier of each of the one or more somas connected to the somajudged by the judging unit 34 as a soma that fires, using the one ormore pieces of feature information applied to the soma-relatedinformation of the soma judged by the judging unit 34 as a soma thatfires or one or more pieces of feature information acquired from the oneor more pieces of feature information, and the connection information inthe connection information storage unit 12.

Note that it is also possible that a soma identified with the somaidentifier acquired by the information transfer unit 71 is judged as asoma that has fired.

Note that the information transfer unit 71 may be the same as theinformation transfer unit 32.

The growth unit 72 performs one or more of soma generation processing,connection information generation processing, and connection informationgrowth processing.

The soma generation processing is processing for generating soma-relatedinformation having a soma identifier, and accumulating it in thesoma-related information storage unit 61. The soma generation processingis, for example, processing for generating a unique soma identifier,ensuring an area of soma-related information containing the unique somaidentifier, in the soma-related information storage unit 61, and copyingone or more pieces of information contained in the soma-relatedinformation of a soma from which division occurred, in the area. It ispreferable that the new soma-related information accumulated in thesoma-related information storage unit 11 has soma positionalinformation, wherein the soma positional information is soma positionalinformation of a position that satisfies a predetermined condition, fromthe position indicated by soma positional information contained insoma-related information of a soma from which division occurred. That isto say, it is preferable that a soma from which division occurred and adivided soma are positioned close to each other.

The soma generation processing is, for example, processing forgenerating soma-related information of a divided soma, which is a newsoma obtained by dividing a soma that satisfies a predeterminedcondition, and accumulating it in the soma-related information storageunit 61. The predetermined condition is, for example, a state in whichthe acquisition by the information transfer unit 71 has occurred for thenumber of times or at the frequency that is large enough to satisfy apredetermined condition. The state in which the number of times orfrequency is large enough to satisfy a predetermined condition is, forexample, a state in which the number of times or frequency is greaterthan or equal to a threshold value or is greater than a threshold value.

The connection information generation processing and the connectioninformation growth processing are described above, and thus, in thisexample, a description thereof has been omitted.

The growth unit 72 may perform an operation similar to that of thegrowth unit 41.

The output information acquiring unit 73 acquires output information,which is information that is output, using the information accepted byeach soma identified with the one or at least two soma identifiersacquired by the information transfer unit 71. For example, the outputinformation acquiring unit 73 performs calculation using, as parameters,information accepted by somas identified with two or more somaidentifiers, thereby acquiring one piece of output information. Examplesof the calculation include addition and multiplication. There is nolimitation on the calculation. There is no limitation on the method foracquiring output information, as long as the output informationacquiring unit 73 uses the information accepted by each soma identifiedwith the one or at least two soma identifiers acquired by theinformation transfer unit 71.

The storage unit 6, the storage unit 8, the soma-related informationstorage unit 61, the connection information storage unit 12, the glialcell information storage unit 13, the output management informationstorage unit 14, the learning condition storage unit 15, the learninginformation storage unit 16, and the firing information storage unit 17are preferably non-volatile storage media, but may be realized also byvolatile storage media.

There is no limitation on the procedure in which information is storedin the storage unit 6 and the like. For example, information may bestored in the storage unit 6 and the like via a storage medium,information transmitted via a communication line or the like may bestored in the storage unit 6 and the like, or information input via aninput device may be stored in the storage unit 6 and the like.

The processing unit 7, the processing unit 9, the growth unit 72, andthe information transfer unit 71 may be realized typically by MPUs,memories, or the like. Typically the processing procedure of theprocessing unit 7 is realized by software, and the software is stored ina storage medium such as a ROM. Note that the processing procedure maybe realized also by hardware (dedicated circuits).

Next, an operation example of the information processing apparatus Bwill be described with reference to the flowchart in FIG. 15. In theflowchart in FIG. 15, a description of the same steps as those in theflowchart in FIG. 15 has been omitted.

(Step S1501) The information transfer unit 71 performs informationtransfer between somas, and the information output unit 51 outputs theoutput information acquired by the output information acquiring unit 73.This processing is referred to as transfer output processing. Thetransfer output processing will be described with reference to theflowchart in FIG. 16.

Note that the procedure is terminated by powering off or an interruptionat the end of the process in the flowchart in FIG. 15.

Next, the transfer output processing in step S1501 will be describedwith reference to the flowchart in FIG. 16.

(Step S1601) The processing unit 9 acquires one or more pieces ofinformation that are to be transferred. The information that is to betransferred is input information or information acquired from the inputinformation, and is, for example, one or more feature amounts acquiredfrom the input information, information of a calculation result in asoma from which transfer was performed, or the like. The information ofa calculation result in a soma from which transfer was performed is aresult of calculation performed by the processing unit 9.

(Step S1602) The information transfer unit 71 acquires a soma identifierof each of the one or more somas to which the information acquired instep S1601 is to be given. The one or more somas are a soma identifierof a soma to which information is given first, or a soma connected to asoma from which information transfer was performed. The soma identifierof a soma to which information is given first is stored, for example, inthe storage unit 8. The soma connected to a soma from which informationtransfer was performed can be acquired from the connection informationin the connection information storage unit 12. The soma identifier of asoma connected to a soma from which information transfer was performedis, for example, a soma identifier that is paired with a soma identifierof a soma from which information transfer was performed, and can beacquired from the connection information storage unit 12.

(Step S1603) The processing unit 9 substitutes 1 for a counter i.

(Step S1604) The processing unit 9 judges whether or not there is ani^(-th) soma identifier in the one or more soma identifiers acquired instep S1602. If there is an i^(-th) soma identifier, the procedureadvances to step S1605, and, if not, the procedure advances to stepS1608.

(Step S1605) The processing unit 9 performs predetermined calculation ona soma identified with the i^(-th) soma identifier using the informationacquired in step S1601, thereby acquiring information in the somaidentified with the soma identifier. This information is informationthat is to be given to a next soma connected to the soma identified withthe i^(-th) soma identifier. There is no limitation on the calculation,as long as it is calculation using, as parameters, the informationacquired in step S1601. The information such as a calculation formulafor performing calculation is stored in the storage unit 8. Theinformation such as a calculation formula for performing calculation maybe managed for each soma, may be managed for each soma group, or may becommon to all somas. The calculation formula is, for example, anincreasing function using, as parameters, the information acquired instep S1601. The calculation formula is, for example, an increasingfunction using, as parameters, two or more pieces of information givenfrom multiple somas. The calculation formula is, for example, a functionthat adds two or more pieces of information given from multiple somas.The calculation formula is, for example, a formula that multiplies theinformation acquired in step S1601 by a probability indicated by theprobability information contained in the soma-related informationcorresponding to each soma.

(Step S1606) The processing unit 9 performs transfer output processingthat starts from the soma identified with the i ^(-th) soma identifier.

(Step S1607) The processing unit 9 increments the counter i by 1. Theprocedure returns to step S1604.

(Step S1608) The output information acquiring unit 37 judges whether ornot to output output information. If output information is to be output,the procedure advances to step S1609, and, if not, the procedure returnsto the upper-level processing.

(Step S1609) The output information acquiring unit 73 acquires outputinformation. For example, the output information acquiring unit 73calculates output information by using an increasing function using, asparameters, calculation results in i somas from the first order to thei^(-th) order (the last order) in the last loop in the transfer outputprocessing in FIG. 16 (acquired in step S1605). Examples of theincreasing function include addition and averaging. For example, theoutput information acquiring unit 73 acquires, as output information,the largest value from calculation results in i somas from the firstorder to the i^(-th) order (the last order) in the last loop in thetransfer output processing in FIG. 16.

(Step S1610) The information output unit 51 outputs the outputinformation acquired in step S1609. The procedure returns to theupper-level processing.

As described above, according to this embodiment, it is possible torealize an information processing apparatus for simulating growth andapoptosis of cells and the like in the brain.

Note that, in this embodiment, the information processing apparatus Bmay not have the apoptosis processing unit 42. Alternatively, in thisembodiment, the information processing apparatus B may not have thegrowth unit 72. That is to say in this embodiment, it is sufficient thatthe information processing apparatus B performs either the growthprocessing or the apoptosis processing.

Furthermore, in this embodiment, as described above, processing forautomatically generating or automatically deleting nodes of a networksuch as a neural network may be performed.

The software that realizes the information processing apparatus B inthis embodiment is the following sort of program. Specifically, thisprogram is a program using a computer-accessible storage mediumincluding: a soma-related information storage unit in which two or morepieces of soma-related information having a soma identifier foridentifying a soma are stored; and a connection information storage unitin which one or more pieces of connection information for specifyingconnection between two or more somas are stored, the program causing acomputer to function as: an input information accepting unit thataccepts input information; an information transfer unit that acquiressoma identifiers of one or more somas that accept information based onthe input information; an output information acquiring unit thatacquires output information, which is information that is output, usingthe information accepted by each soma identified with the one or moresoma identifiers acquired by the information transfer unit; aninformation output unit that outputs the output information acquired bythe output information acquiring unit; and a growth unit that performsone or more of soma generation processing for generating soma-relatedinformation having a soma identifier, and accumulating the informationin the soma-related information storage unit, connection informationgeneration processing for generating connection information, andaccumulating the information in the connection information storage unit,and connection information growth processing for growing connectioninformation.

FIG. 17 shows the external appearance of a computer that executes theprograms described in this specification to realize the informationprocessing apparatus A in the foregoing various embodiments. Theforegoing embodiments may be realized using computer hardware and acomputer program executed thereon. FIG. 17 is a schematic view of acomputer system 300. FIG. 18 is a block diagram of the system 300.

In FIG. 17, the computer system 300 includes a computer 301 including aCD-ROM drive 3012, a keyboard 302, a mouse 303, and a monitor 304.

In FIG. 18, the computer 301 includes the CD-ROM drive 3012, an MPU3013, a bus 3014, a ROM 3015, a RAM 3016, and a hard disk 3017. In theROM 3015, a program such as a boot up program is stored. The RAM 3016 isconnected to the MPU 3013 and is a memory in which a command of anapplication program is temporarily stored and a temporary storage areais provided. In the hard disk 3017, typically an application program, asystem program, and data are stored. Although not shown, the computer301 may further include a network card that provides connection to aLAN.

The programs for causing the computer system 300 to execute thefunctions of the information processing apparatus in the foregoingembodiments may be stored in a CD-ROM 3101 that is inserted into theCD-ROM drive 3012, and be transmitted to the hard disk 3017.Alternatively, the programs may be transmitted via a network (not shown)to the computer 301 and stored in the hard disk 3017. At the time ofexecution, the programs are loaded into the RAM 3016. The programs maybe loaded from the CD-ROM 3101, or directly from a network.

The programs do not necessarily have to include, for example, anoperating system (OS) or a third party program to cause the computer 301to execute the functions of the information processing apparatus in theforegoing embodiments. The programs may only include a command portionto call an appropriate module in a controlled mode and obtain desiredresults. The manner in which the computer system 300 operates is wellknown, and thus a detailed description thereof has been omitted.

Furthermore, the computer that executes the programs may be a singlecomputer, or may be multiple computers. That is to say, centralizedprocessing may be performed, or distributed processing may be performed.

In the foregoing embodiments, each process may be realized ascentralized processing using a single apparatus, or may be realized asdistributed processing using multiple apparatuses.

INDUSTRIAL APPLICABILITY

As described above, the information processing apparatus according tothe present invention has an effect that it is possible to realize aninformation processing apparatus for simulating growth and the like ofcells and the like in the brain, and thus this apparatus is useful as aninformation processing apparatus and the like.

LIST OF REFERENCE NUMERALS

A, B Information processing apparatus

1, 6, 8 Storage unit

2 Accepting unit

3, 7, 9 Processing unit

5 Output unit

11, 61 Soma-related information storage unit

12 Soma group information storage unit

13 Connection information storage unit

14 Glial cell information storage unit

15 Firing start point information storage unit

16 Output management information storage unit

17 Learning condition storage unit

18 Learning information storage unit

19 Firing information storage unit

20 Used connection information storage unit

21 Input information accepting unit

31 Feature information acquiring unit

32, 71 Information transfer unit

33 Soma calculating unit

34 Judging unit

35 Firing probability changing unit

36 Firing pattern acquiring unit

37, 73 Output information acquiring unit

38 Control unit

39 Learning detecting unit

40 Learning information accumulating unit

41, 72 Growth unit

42 Apoptosis processing unit

43 Firing information accumulating unit

51 Information output unit

321 Firing start point soma determining part

322 Connection detecting part

323 Transfer information acquiring part

1. An information processing apparatus comprising: a soma-relatedinformation storage unit in which two or more pieces of soma-relatedinformation having a soma identifier for identifying a soma are stored;a connection information storage unit in which one or more pieces ofconnection information for specifying connection between two or moresomas are stored; an input information accepting unit that accepts inputinformation; an information transfer unit that acquires soma identifiersof one or more somas that accept information based on the inputinformation; an output information acquiring unit that acquires outputinformation, which is information that is output, using the informationaccepted by each soma identified with the one or more soma identifiersacquired by the information transfer unit; an information output unitthat outputs the output information acquired by the output informationacquiring unit; and a growth unit that performs one or more of somageneration processing for generating soma-related information having asoma identifier, and accumulating the information in the soma-relatedinformation storage unit, connection information generation processingfor generating connection information, and accumulating the informationin the connection information storage unit, and connection informationgrowth processing for growing connection information.
 2. The informationprocessing apparatus according to claim 1, wherein the growth unitperforms soma generation processing for generating soma-relatedinformation of a divided soma, which is a new soma obtained by dividinga soma that satisfies a predetermined condition, and accumulating theinformation in the soma-related information storage unit, and connectioninformation generation processing for generating connection informationfor connecting a soma that satisfies the condition and a divided soma,and accumulating the information in the connection information storageunit.
 3. The information processing apparatus according to claim 1,further comprising: a glial cell information storage unit in which oneor more pieces of glial cell information having a soma identifier foridentifying a soma for connection, or a connection informationidentifier for identifying connection information for connection arestored, wherein the growth unit performs one or more of soma generationprocessing for generating soma-related information of a divided soma,which is a new soma obtained by dividing a soma connected to glial cellinformation that satisfies a predetermined condition, and accumulatingthe information in the soma-related information storage unit, andconnection information growth processing for growing an axon or adendrite connected to glial cell information that satisfies apredetermined condition.
 4. The information processing apparatusaccording to claim 1, wherein the soma-related information has somapositional information indicating a position of a soma, one or morepieces of dendrite information, and one or more pieces of axoninformation, the dendrite information has a dendrite identifier anddendrite positional information indicating a position of a dendrite, theaxon information has an axon identifier and axon positional informationindicating a position of an axon, at least some of the one or morepieces of connection information in the connection information storageunit have an axon identifier of an axon of one soma and a dendriteidentifier of a dendrite of another soma, and the growth unit performsconnection information growth processing for changing the axonpositional information so as to allow an axon to extend or changing thedendrite positional information so as to allow a dendrite to extend,and, in a case in which axon positional information of an axon of onesoma and dendrite positional information of a dendrite of another somaare close to each other enough to satisfy a predetermined condition,performs connection information generation processing for generatingconnection information for specifying connection between the axon of theone soma and the dendrite of the other soma, and accumulating theinformation in the connection information storage unit.
 5. Theinformation processing apparatus according to claim 4, wherein thesoma-related information has a soma group identifier for identifying asoma group, which is a group to which a soma belongs, the informationprocessing apparatus further comprises a soma group information storageunit in which two or more pieces of soma group information, each havinga soma group identifier for identifying a soma group and goalinformation for specifying a destination to which an axon or a dendriteconnected to a soma belonging to the soma group extends, are stored, andthe growth unit changes the axon positional information or the dendritepositional information such that an axon or a dendrite extends to adestination specified with the goal information contained in the somagroup information of a soma group to which a soma connected to the axonor the dendrite belongs.
 6. The information processing apparatusaccording to claim 3, wherein the glial cell information has glial cellpositional information for specifying a position of a glial cell, andthe growth unit changes the axon positional information of an axonidentified with a connection information identifier contained in theglial cell information, such that the position becomes closer to aposition indicated by the glial cell positional information contained inthe glial cell information.
 7. The information processing apparatusaccording to claim 1, further comprising: an apoptosis processing unitthat deletes soma-related information from the soma-related informationstorage unit according to a predetermined condition.
 8. The informationprocessing apparatus according to claim 7, wherein, in a case in whichthe amount of soma-related information stored in the soma-relatedinformation storage unit is large enough to satisfy a predeterminedcondition, the apoptosis processing unit deletes the soma-relatedinformation from the soma-related information storage unit.
 9. Theinformation processing apparatus according to claim 7, furthercomprising: a firing information storage unit in which one or morepieces of firing information having a soma identifier for identifying asoma that has fired are stored; and a firing information accumulatingunit that configures firing information having a soma identifier foridentifying a soma judged as a soma that fires, and accumulates thefiring information in the firing information storage unit, wherein,using the one or more pieces of firing information in the firinginformation storage unit, the apoptosis processing unit determines asoma that is not connected to another soma, a dendrite, or an axon,determines a soma connected to an axon that does not reach apredetermined goal, or determines a soma that has fired for the numberof times that is small enough to satisfy a predetermined condition, anddeletes soma-related information having a soma identifier of thedetermined soma, from the soma-related information storage unit.
 10. Theinformation processing apparatus according to claim 1, wherein, in thesoma-related information storage unit, firing condition informationrelated to a condition for the soma to fire is also stored, theinformation processing apparatus further comprises: an output managementinformation storage unit in which one or more pieces of outputmanagement information having an output condition, which is a conditionfor output using a firing pattern having one or more soma identifiers,and output information, which is information that is output, are stored;and a feature information acquiring unit that acquires one or morepieces of feature information from the input information, theinformation transfer unit acquires the one or more pieces of featureinformation acquired by the feature information acquiring unit and oneor more soma identifiers each for identifying a soma that fires first,and acquires one or more pieces of feature information given from one ormore other somas or one or more pieces of feature information acquiredfrom the one or more pieces of feature information, and a somaidentifier of each of one or more somas that are to be subjected tojudgment of firing, the information processing apparatus furthercomprises: a judging unit that, using the one or more pieces of featureinformation acquired by the information transfer unit, and firingcondition information that is paired with the one or more somaidentifiers acquired by the information transfer unit, judges whether ornot the soma identified with each of the soma identifiers fires; and afiring pattern acquiring unit that acquires a firing pattern containingone or more soma identifiers each for identifying a soma judged by thejudging unit as a soma that fires, the output information acquiring unitacquires, from the output management information storage unit, outputinformation corresponding to the firing pattern acquired by the firingpattern acquiring unit, the information transfer unit acquires the somaidentifier of each of the one or more somas connected to the soma judgedby the judging unit as a soma that fires, using the one or more piecesof feature information applied to soma-related information of the somajudged by the judging unit as a soma that fires or one or more pieces offeature information acquired from the one or more pieces of featureinformation, and the connection information in the connectioninformation storage unit, and the processing by the judging unit, theprocessing by the firing pattern acquiring unit, and the processing bythe information transfer unit are repeated twice or more.
 11. Theinformation processing apparatus according to claim 10, wherein, in theoutput management information storage unit, one or more pieces of outputmanagement information having an output condition, which is a conditionusing a firing pattern having one or more soma identifiers andinformation related to one or more pieces of additional information thatis additional information, and output information, which is informationthat is output, are stored, the input information accepting unit acceptsone or more pieces of additional information, and the output informationacquiring unit determines an output condition that matches the one ormore soma identifiers acquired by the firing pattern acquiring unit andthe one or more pieces of additional information accepted by the inputinformation accepting unit, and acquires output information that ispaired with the output condition.
 12. The information processingapparatus according to claim 1, wherein the output information containsany of emotion information related to emotion of a person, intentioninformation indicating intention of a person, and behavior informationrelated to body movements of a person.
 13. An information processingmethod using a storage medium including: a soma-related informationstorage unit in which two or more pieces of soma-related informationhaving a soma identifier for identifying a soma are stored; and aconnection information storage unit in which one or more pieces ofconnection information for specifying connection between two or moresomas are stored, the method realized by an input information acceptingunit, an information transfer unit, an output information acquiringunit, an information output unit, and a growth unit, comprising: aninput information accepting step of the input information accepting unitaccepting input information; an information transfer step of theinformation transfer unit acquiring soma identifiers of one or moresomas that accept information based on the input information; an outputinformation acquiring step of the output information acquiring unitacquiring output information, which is information that is output, usingthe information accepted by each soma identified with the one or moresoma identifiers acquired in the information transfer step, aninformation output step of the information output unit outputting theoutput information acquired in the output information acquiring step,and a growth step of the growth unit performing one or more of somageneration processing for generating soma-related information having asoma identifier, and accumulating the information in the soma-relatedinformation storage unit, connection information generation processingfor generating connection information, and accumulating the informationin the connection information storage unit, and connection informationgrowth processing for growing connection information.
 14. A programusing a computer-accessible storage medium including: a soma-relatedinformation storage unit in which two or more pieces of soma-relatedinformation having a soma identifier for identifying a soma are stored;and a connection information storage unit in which one or more pieces ofconnection information for specifying connection between two or moresomas are stored, the program causing a computer to function as: aninput information accepting unit that accepts input information; aninformation transfer unit that acquires soma identifiers of one or moresomas that accept information based on the input information; an outputinformation acquiring unit that acquires output information, which isinformation that is output, using the information accepted by each somaidentified with the one or more soma identifiers acquired by theinformation transfer unit; an information output unit that outputs theoutput information acquired by the output information acquiring unit;and a growth unit that performs one or more of soma generationprocessing for generating soma-related information having a somaidentifier, and accumulating the information in the soma-relatedinformation storage unit, connection information generation processingfor generating connection information, and accumulating the informationin the connection information storage unit, and connection informationgrowth processing for growing connection information.